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com.microsoft.ml

spark

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package spark

Microsoft Machine Learning on Apache Spark (MMLSpark)

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Type Members

  1. class AnalyzeImage extends CognitiveServicesBase with HasImageUrl with HasInternalJsonOutputParser with HasCognitiveServiceInput

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  2. class AssembleFeatures extends Estimator[AssembleFeaturesModel] with HasFeaturesCol with Wrappable with DefaultParamsWritable

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    Creates a vector column of features from a collection of feature columns

  3. class AssembleFeaturesModel extends Model[AssembleFeaturesModel] with Params with ConstructorWritable[AssembleFeaturesModel]

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    Model produced by AssembleFeatures.

  4. abstract class AsyncClient extends BaseClient

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  5. class AsyncHTTPClient extends AsyncClient with HTTPClient

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  6. class BasicDatasetGenerationConstraints extends HasDatasetGenerationConstraints

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    Basic constraints for generating a dataset.

  7. class BatchIterator[T] extends Iterator[List[T]]

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  8. case class Benchmark(name: String, value: Double, precision: Double, higherIsBetter: Boolean = true) extends Product with Serializable

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  9. abstract class Benchmarks extends TestBase

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  10. class BestModel extends Model[BestModel] with ConstructorWritable[BestModel]

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    Model produced by FindBestModel.

    Model produced by FindBestModel.

    Annotations
    @InternalWrapper()
  11. case class BingImage(accentColor: String, contentSize: String, contentUrl: String, datePublished: String, encodingFormat: String, height: Int, hostPageDisplayUrl: String, hostPageUrl: String, id: String, imageId: String, imageInsightsToken: String, insightsMetadata: String, name: String, thumbnail: BingMediaSize, thumbnailUrl: String, webSearchUrl: String, width: Int) extends Product with Serializable

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  12. class BingImageSearch extends CognitiveServicesBase with HasCognitiveServiceInput with HasInternalJsonOutputParser

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    Annotations
    @InternalWrapper()
  13. case class BingImagesResponse(_type: String, instrumentation: BingInstrumentation, webSearchUrl: String, totalEstimatedMatches: Int, nextOffset: Int, value: Seq[BingImage], pivotSuggestions: Seq[BingPivot], queryExpansions: Seq[BingQuery], relatedSearches: Seq[BingQuery]) extends Product with Serializable

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  14. case class BingInstrumentation(_type: String) extends Product with Serializable

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  15. case class BingMediaSize(height: Int, width: Int) extends Product with Serializable

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  16. case class BingPivot(pivot: String, suggestions: Seq[BingQuery]) extends Product with Serializable

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  17. case class BingQuery(displayText: String, searchLink: String, text: String, thumbnail: BingThumbnail, webSearchUrl: String) extends Product with Serializable

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  18. case class BingThumbnail(thumbnailUrl: String) extends Product with Serializable

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  19. class Blur extends ImageTransformerStage

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    Blurs the image using a box filter.

    Blurs the image using a box filter. The params are a map of the dimensions of the blurring box. Please refer to OpenCV for more information.

  20. class BrainScriptBuilder extends AnyRef

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    Utility methods for manipulating the BrainScript and overrides configs output to disk.

  21. case class BrainScriptConfig(name: String, text: Seq[String]) extends Product with Serializable

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  22. class CNTKCommandBuilder extends CNTKCommandBuilderBase

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  23. abstract class CNTKCommandBuilderBase extends AnyRef

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  24. class CNTKConfig extends MMLConfig

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  25. class CNTKFunctionParam extends ComplexParam[SerializableFunction]

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    Param for ByteArray.

    Param for ByteArray. Needed as spark has explicit params for many different types but not ByteArray.

  26. class CNTKLearner extends Estimator[CNTKModel] with CNTKParams with Wrappable

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    Annotations
    @InternalWrapper()
  27. class CNTKModel extends Model[CNTKModel] with ComplexParamsWritable with HasMiniBatcher with Wrappable

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    Annotations
    @InternalWrapper()
  28. trait CNTKParams extends Params

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  29. class Cacher extends Transformer with Wrappable with DefaultParamsWritable

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  30. class CheckpointData extends Transformer with CheckpointDataParams

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    Cache the dataset at this point to memory or memory and disk

  31. trait CheckpointDataParams extends Wrappable with DefaultParamsWritable

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  32. class ClassBalancer extends Estimator[ClassBalancerModel] with DefaultParamsWritable with HasInputCol with HasOutputCol

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    An estimator that calculates the weights for balancing a dataset.

    An estimator that calculates the weights for balancing a dataset. For example, if the negative class is half the size of the positive class, the weights will be 2 for rows with negative classes and 1 for rows with positive classes. these weights can be used in weighted classifiers and regressors to correct for heavilty skewed datasets. The inputCol should be the labels of the classes, and the output col will be the requisite weights.

  33. class ClassBalancerModel extends Model[ClassBalancerModel] with ConstructorWritable[ClassBalancerModel]

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  34. case class ClassifierTrainParams(parallelism: String, numIterations: Int, learningRate: Double, numLeaves: Int, maxBin: Int, baggingFraction: Double, baggingFreq: Int, baggingSeed: Int, earlyStoppingRound: Int, featureFraction: Double, maxDepth: Int, minSumHessianInLeaf: Double, numMachines: Int, objective: String, modelString: String) extends TrainParams with Product with Serializable

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    Defines the Booster parameters passed to the LightGBM classifier.

  35. class CleanMissingData extends Estimator[CleanMissingDataModel] with HasInputCols with HasOutputCols with Wrappable with DefaultParamsWritable

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    Removes missing values from input dataset.

    Removes missing values from input dataset. The following modes are supported: Mean - replaces missings with mean of fit column Median - replaces missings with approximate median of fit column Custom - replaces missings with custom value specified by user For mean and median modes, only numeric column types are supported, specifically: Int, Long, Float, Double For custom mode, the types above are supported and additionally: String, Boolean

  36. class CleanMissingDataModel extends Model[CleanMissingDataModel] with ConstructorWritable[CleanMissingDataModel]

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    Model produced by CleanMissingData.

  37. class Cluster extends AnyRef

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  38. abstract class CognitiveServicesBase extends CognitiveServicesBaseWithoutHandler with HasHandler

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  39. abstract class CognitiveServicesBaseWithoutHandler extends Transformer with HTTPParams with HasOutputCol with HasURL with ComplexParamsWritable with HasSubscriptionKey with HasErrorCol

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  40. class ColorFormat extends ImageTransformerStage

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    Converts an image from one color space to another, eg COLOR_BGR2GRAY.

    Converts an image from one color space to another, eg COLOR_BGR2GRAY. Refer to OpenCV for more information.

  41. class ColumnNamesToFeaturize extends Serializable

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    Class containing the list of column names to perform special featurization steps for.

    Class containing the list of column names to perform special featurization steps for. colNamesToHash - List of column names to hash. colNamesToDuplicateForMissings - List of column names containing doubles to duplicate so we can remove missing values from them. colNamesToTypes - Map of column names to their types. colNamesToCleanMissings - List of column names to clean missing values from (ignore). colNamesToVectorize - List of column names to vectorize using FastVectorAssembler. categoricalColumns - List of categorical columns to pass through or turn into indicator array. conversionColumnNamesMap - Map from old column names to new. addedColumnNamesMap - Map from old columns to newly generated columns for featurization.

    Annotations
    @SerialVersionUID()
  42. class ComputeModelStatistics extends Transformer with ComputeModelStatisticsParams

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    Evaluates the given scored dataset.

  43. trait ComputeModelStatisticsParams extends Wrappable with DefaultParamsWritable with HasLabelCol with HasScoresCol with HasScoredLabelsCol with HasEvaluationMetric

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  44. class ComputePerInstanceStatistics extends Transformer with ComputePerInstanceStatisticsParams

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    Evaluates the given scored dataset with per instance metrics.

    Evaluates the given scored dataset with per instance metrics.

    The Regression metrics are: - L1_loss - L2_loss

    The Classification metrics are: - log_loss

  45. trait ComputePerInstanceStatisticsParams extends Wrappable with DefaultParamsWritable with HasLabelCol with HasScoresCol with HasScoredLabelsCol with HasScoredProbabilitiesCol with HasEvaluationMetric

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  46. abstract class Configuration extends AnyRef

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  47. class Consolidator[T] extends AnyRef

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  48. trait ConstructorReadable[T <: ConstructorWritable[_]] extends MLReadable[T]

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  49. class ConstructorReader[T] extends MLReader[T]

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  50. trait ConstructorWritable[S <: PipelineStage] extends MLWritable

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    This trait allows you to easily add serialization to your Spark Models, assuming that they are completely parameterized by their constructor.

    This trait allows you to easily add serialization to your Spark Models, assuming that they are completely parameterized by their constructor. The main two fields required ate the TypeTag that allows the writer to inspect the constructor to get the types that need to be serialized, the actual objects that are serialized need to be defined in the field objectsToSave.

  51. abstract class ConstructorWriter[S <: PipelineStage] extends MLWriter

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  52. class ContextObjectInputStream extends ObjectInputStream

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  53. class CropImage extends ImageTransformerStage

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    Crops the image for processing.

    Crops the image for processing. The parameters are: "x" - First dimension; start of crop "y" - second dimension - start of crop "height" -height of cropped image "width" - width of cropped image "stageName" - "crop"

  54. class CustomInputParser extends HTTPInputParser with ComplexParamsWritable

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  55. class CustomOutputParser extends HTTPOutputParser with ComplexParamsWritable

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  56. class DataConversion extends Transformer with Wrappable with DefaultParamsWritable

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    Converts the specified list of columns to the specified type.

    Converts the specified list of columns to the specified type. Returns a new DataFrame with the converted columns

  57. trait DataFrameEquality extends TestBase

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  58. case class DataFrameServingExtensions(df: DataFrame) extends Product with Serializable

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  59. class DataFrameSugars extends AnyRef

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  60. case class DataStreamReaderExtensions(dsr: DataStreamReader) extends Product with Serializable

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  61. case class DataStreamWriterExtensions[T](dsw: DataStreamWriter[T]) extends Product with Serializable

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  62. abstract class DataWriter extends AnyRef

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  63. case class DatasetMissingValuesGenerationOptions(percentMissing: Double, columnTypesWithMissings: ColumnOptions.ValueSet, dataTypesWithMissings: DataOptions.ValueSet) extends Product with Serializable

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  64. case class DatasetOptions(columnTypes: ColumnOptions.ValueSet, dataTypes: DataOptions.ValueSet, missingValuesOptions: DatasetMissingValuesGenerationOptions) extends Product with Serializable

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    Options used to specify how a dataset will be generated.

    Options used to specify how a dataset will be generated. This contains information on what the data and column types (specified as flags) for generating a dataset will be limited to. It also contain options for all possible missing values generation and options for how values will be generated.

  65. case class DetectEntitiesScore(id: String, entities: Seq[Entity]) extends Product with Serializable

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  66. class DetectFace extends CognitiveServicesBase with HasImageUrl with HasServiceParams with HasCognitiveServiceInput with HasInternalJsonOutputParser

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  67. case class DetectLanguageScore(id: String, detectedLanguages: Seq[DetectedLanguage]) extends Product with Serializable

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  68. case class DetectedLanguage(name: String, iso6391Name: String, score: Double) extends Product with Serializable

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  69. class DiscreteHyperParam[T] extends Dist[T]

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  70. abstract class Dist[T] extends AnyRef

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    Represents a distribution of values.

    Represents a distribution of values.

    T

    The type T of the values generated.

  71. class DoubleRangeHyperParam extends RangeHyperParam[Double]

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  72. class DropColumns extends Transformer with Wrappable with DefaultParamsWritable

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    DropColumns takes a dataframe and a list of columns to drop as input and returns a dataframe comprised of only those columns not listed in the input list.

    DropColumns takes a dataframe and a list of columns to drop as input and returns a dataframe comprised of only those columns not listed in the input list.

  73. class DynamicBufferedBatcher[T] extends Iterator[List[T]]

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  74. class DynamicMiniBatchTransformer extends Transformer with MiniBatchBase

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  75. class EnsembleByKey extends Transformer with Wrappable with DefaultParamsWritable

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  76. case class Entity(name: String, matches: Seq[Match], wikipediaLanguage: String, wikipediaId: String, wikipediaUrl: String, bingId: String) extends Product with Serializable

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  77. case class EntityData(content: Array[Byte], contentEncoding: Option[HeaderData], contentLength: Option[Long], contentType: Option[HeaderData], isChunked: Boolean, isRepeatable: Boolean, isStreaming: Boolean) extends Product with Serializable

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  78. class EntityDetector extends TextAnalyticsBase

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  79. class Explode extends Transformer with HasInputCol with HasOutputCol with Wrappable with DefaultParamsWritable

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  80. class Featurize extends Estimator[PipelineModel] with Wrappable with DefaultParamsWritable

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    Featurizes a dataset.

    Featurizes a dataset. Converts the specified columns to feature columns.

  81. class FindBestModel extends Estimator[BestModel] with FindBestModelParams

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    Evaluates and chooses the best model from a list of models.

    Evaluates and chooses the best model from a list of models.

    Annotations
    @InternalWrapper()
  82. trait FindBestModelParams extends Wrappable with ComplexParamsWritable with HasEvaluationMetric

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  83. class FindSimilarFace extends CognitiveServicesBase with HasServiceParams with HasMaxNumOfCandidatesReturned with HasFaceIds with HasCognitiveServiceInput with HasInternalJsonOutputParser

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  84. class FixedBatcher[T] extends Iterator[List[T]]

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  85. class FixedBufferedBatcher[T] extends Iterator[List[T]]

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  86. class FixedMiniBatchTransformer extends Transformer with MiniBatchBase

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  87. class FlattenBatch extends Transformer with Wrappable with DefaultParamsWritable

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  88. class Flip extends ImageTransformerStage

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    Flips the image

  89. class FloatRangeHyperParam extends RangeHyperParam[Float]

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  90. class GaussianKernel extends ImageTransformerStage

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    Applies gaussian kernel to blur the image.

    Applies gaussian kernel to blur the image. Please refer to OpenCV for detailed information about the parameters and their allowable values.

  91. class GenerateDataType extends Serializable

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    Generates the specified random data type.

  92. class GenerateThumbnails extends CognitiveServicesBase with HasImageUrl with HasWidth with HasHeight with HasSmartCropping with HasInternalJsonOutputParser with HasCognitiveServiceInput

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  93. class GridSpace extends ParamSpace

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    Represents a parameter grid for tuning with discrete values.

    Represents a parameter grid for tuning with discrete values. Can be generated with the ParamGridBuilder.

  94. class GroupFaces extends CognitiveServicesBase with HasServiceParams with HasFaceIds with HasCognitiveServiceInput with HasInternalJsonOutputParser

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  95. abstract class HTTPInputParser extends Transformer with HasOutputCol with HasInputCol

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  96. abstract class HTTPOutputParser extends Transformer with HasInputCol with HasOutputCol

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  97. trait HTTPParams extends Wrappable

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  98. case class HTTPRequestData(requestLine: RequestLineData, headers: Array[HeaderData], entity: Option[EntityData]) extends Product with Serializable

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  99. case class HTTPResponseData(headers: Array[HeaderData], entity: Option[EntityData], statusLine: StatusLineData, locale: String) extends Product with Serializable

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  100. class HTTPTransformer extends Transformer with HTTPParams with HasInputCol with HasOutputCol with HasHandler with ComplexParamsWritable

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  101. trait Handler extends AnyRef

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  102. trait HasCellSize extends Params

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  103. trait HasCognitiveServiceInput extends HasURL with HasSubscriptionKey

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  104. trait HasDatasetGenerationConstraints extends AnyRef

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    Specifies the trait for constraints on generating a dataset.

  105. trait HasDetectOrientation extends HasServiceParams

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  106. trait HasErrorCol extends Params

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  107. trait HasEvaluationMetric extends Wrappable

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  108. trait HasFaceIds extends HasServiceParams

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  109. trait HasFeaturesCol extends Wrappable

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  110. trait HasHandler extends Params

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  111. trait HasHeight extends HasServiceParams

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  112. trait HasImageUrl extends HasServiceParams

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  113. trait HasInputCol extends Wrappable

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  114. trait HasInputCols extends Wrappable

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  115. trait HasInternalJsonOutputParser extends AnyRef

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  116. trait HasLabelCol extends Wrappable

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  117. trait HasLanguage extends HasServiceParams

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  118. trait HasMaxNumOfCandidatesReturned extends HasServiceParams

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  119. trait HasMiniBatcher extends Params

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  120. trait HasModifier extends Params

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  121. trait HasOutputCol extends Wrappable

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  122. trait HasOutputCols extends Wrappable

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  123. trait HasScoredLabelsCol extends Wrappable

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  124. trait HasScoredProbabilitiesCol extends Wrappable

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  125. trait HasScoresCol extends Wrappable

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  126. trait HasServiceParams extends Params

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  127. trait HasSmartCropping extends HasServiceParams

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  128. trait HasSubscriptionKey extends HasServiceParams

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  129. trait HasURL extends Wrappable

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  130. trait HasWidth extends HasServiceParams

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  131. class HdfsWriter extends SingleFileResolver

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  132. case class HeaderData(name: String, value: String) extends Product with Serializable

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  133. class HyperparamBuilder extends AnyRef

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    Specifies the search space for hyperparameters.

  134. class IdentifyFaces extends CognitiveServicesBase with HasServiceParams with HasMaxNumOfCandidatesReturned with HasFaceIds with HasCognitiveServiceInput with HasInternalJsonOutputParser

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  135. class ImageFeaturizer extends Transformer with HasInputCol with HasOutputCol with Wrappable with ComplexParamsWritable

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    The ImageFeaturizer relies on a CNTK model to do the featurization, one can set this model using the modelLocation parameter.

    The ImageFeaturizer relies on a CNTK model to do the featurization, one can set this model using the modelLocation parameter. To map the nodes of the CNTK model onto the standard "layers" structure of a feed forward neural net, one needs to supply a list of node names that range from the output node, back towards the input node of the CNTK Function. This list does not need to be exhaustive, and is provided to you if you use a model downloaded from the ModelDownloader, one can find this layer list in the schema of the downloaded model.

    The ImageFeaturizer takes an input column of images (the type returned by the ImageReader), and automatically resizes them to fit the CMTKModel's inputs. It then feeds them through a pre-trained CNTK model. One can truncate the model using the cutOutputLayers parameter that determines how many layers to truncate from the output of the network. For example, layer=0 means that no layers are removed, layer=2 means that the image featurizer returns the activations of the layer that is two layers from the output layer.

    Annotations
    @InternalWrapper()
  136. class ImageLIME extends Transformer with HasInputCol with HasOutputCol with HasLabelCol with Wrappable with ComplexParamsWritable with HasModifier with HasCellSize

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    Distributed implementation of Local Interpretable Model-Agnostic Explanations (LIME)

    Distributed implementation of Local Interpretable Model-Agnostic Explanations (LIME)

    https://arxiv.org/pdf/1602.04938v1.pdf

  137. class ImageSetAugmenter extends Transformer with HasInputCol with HasOutputCol with DefaultParamsWritable

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  138. class ImageTransformer extends Transformer with HasInputCol with HasOutputCol with Wrappable with DefaultParamsWritable

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    Image processing stage.

    Image processing stage. Please refer to OpenCV for additional information

    Annotations
    @InternalWrapper()
  139. abstract class ImageTransformerStage extends Serializable

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    Image processing stage.

  140. class IndexToValue extends Transformer with HasInputCol with HasOutputCol with Wrappable with DefaultParamsWritable

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    This class takes in a categorical column with MML style attibutes and then transforms it back to the original values.

    This class takes in a categorical column with MML style attibutes and then transforms it back to the original values. This extends MLLIB IndexToString by allowing the transformation back to any types of values.

  141. case class InputData(format: String, path: String, shapes: Map[String, InputShape]) extends Product with Serializable

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  142. case class InputShape(dim: Int, form: String) extends Product with Serializable

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  143. class IntRangeHyperParam extends RangeHyperParam[Int]

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  144. class InternalWrapper extends Annotation with StaticAnnotation

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    Generate the internal wrapper for a given class.

    Generate the internal wrapper for a given class. Used for complicated wrappers, where the basic functionality is auto-generated, and the rest is added in the inherited wrapper.

  145. class JSONInputParser extends HTTPInputParser with HasURL with ComplexParamsWritable

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  146. class JSONOutputParser extends HTTPOutputParser with ComplexParamsWritable

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  147. class KeyPhraseExtractor extends TextAnalyticsBase

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  148. case class KeyPhraseScore(id: String, keyPhrases: Seq[String]) extends Product with Serializable

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  149. class Lambda extends Transformer with Wrappable with ComplexParamsWritable

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  150. class LanguageDetector extends TextAnalyticsBase

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  151. class LightGBMBooster extends Serializable

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    Represents a LightGBM Booster learner

  152. class LightGBMClassificationModel extends ProbabilisticClassificationModel[Vector, LightGBMClassificationModel] with ConstructorWritable[LightGBMClassificationModel]

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    Model produced by LightGBMClassifier.

    Model produced by LightGBMClassifier.

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    @InternalWrapper()
  153. class LightGBMClassifier extends ProbabilisticClassifier[Vector, LightGBMClassifier, LightGBMClassificationModel] with LightGBMParams

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    Trains a LightGBM Binary Classification model, a fast, distributed, high performance gradient boosting framework based on decision tree algorithms.

    Trains a LightGBM Binary Classification model, a fast, distributed, high performance gradient boosting framework based on decision tree algorithms. For more information please see here: https://github.com/Microsoft/LightGBM. For parameter information see here: https://github.com/Microsoft/LightGBM/blob/master/docs/Parameters.rst

    Annotations
    @InternalWrapper()
  154. trait LightGBMParams extends Wrappable with DefaultParamsWritable

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    Defines common parameters across all LightGBM learners.

  155. class LightGBMRegressionModel extends RegressionModel[Vector, LightGBMRegressionModel] with ConstructorWritable[LightGBMRegressionModel]

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    Model produced by LightGBMRegressor.

    Model produced by LightGBMRegressor.

    Annotations
    @InternalWrapper()
  156. class LightGBMRegressor extends BaseRegressor[Vector, LightGBMRegressor, LightGBMRegressionModel] with LightGBMParams

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    Trains a LightGBM Regression model, a fast, distributed, high performance gradient boosting framework based on decision tree algorithms.

    Trains a LightGBM Regression model, a fast, distributed, high performance gradient boosting framework based on decision tree algorithms. For more information please see here: https://github.com/Microsoft/LightGBM. For parameter information see here: https://github.com/Microsoft/LightGBM/blob/master/docs/Parameters.rst Note: The application parameter supports the following values:

    • regression_l2, L2 loss, alias=regression, mean_squared_error, mse, l2_root, root_mean_squared_error, rmse
    • regression_l1, L1 loss, alias=mean_absolute_error, mae
    • huber, Huber loss
    • fair, Fair loss
    • poisson, Poisson regression
    • quantile, Quantile regression
    • mape, MAPE loss, alias=mean_absolute_percentage_error
    • gamma, Gamma regression with log-link. It might be useful, e.g., for modeling insurance claims severity, or for any target that might be gamma-distributed
    • tweedie, Tweedie regression with log-link. It might be useful, e.g., for modeling total loss in insurance, or for any target that might be tweedie-distributed
    Annotations
    @InternalWrapper()
  157. trait LinuxOnly extends TestBase

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  158. class LocalWriter extends SingleFileResolver

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  159. class LongRangeHyperParam extends RangeHyperParam[Long]

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  160. class MMLConfig extends Configuration

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  161. class MPICommandBuilder extends CNTKCommandBuilderBase with MPIConfiguration

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  162. trait MPIConfiguration extends AnyRef

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  163. case class Match(text: String, offset: Int, length: Int) extends Product with Serializable

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  164. class MetricsLogger extends AnyRef

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    Helper class for logging metrics to log4j.

  165. trait MiniBatchBase extends Transformer with DefaultParamsWritable with Wrappable

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  166. class ModelDownloader extends Client

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    Class for downloading models from a server to Local or HDFS

  167. class ModelNotFoundException extends FileNotFoundException

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    Exception returned if a repo cannot find the file

  168. case class ModelSchema(name: String, dataset: String, modelType: String, uri: URI, hash: String, size: Long, inputNode: Int, numLayers: Int, layerNames: Array[String]) extends Schema with Product with Serializable

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    Class representing the schema of a CNTK model

    Class representing the schema of a CNTK model

    name

    name of the model architecture

    dataset

    dataset the model was trained on

    modelType

    type of problem the model is suited for eg: (image, text, sound, sentiment etc)

    uri

    location of the underlying file (local, HDFS, or HTTP)

    hash

    sha256 hash of the underlying file

    size

    size in bytes of the underlying file

    inputNode

    the node which represents the input

    numLayers

    the number of layers of the model

    layerNames

    the names nodes that represent layers in the network

  169. class MultiColumnAdapter extends Estimator[PipelineModel] with Wrappable with ComplexParamsWritable

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    The MultiColumnAdapter takes a unary pipeline stage and a list of input output column pairs and applies the pipeline stage to each input column after being fit

    The MultiColumnAdapter takes a unary pipeline stage and a list of input output column pairs and applies the pipeline stage to each input column after being fit

  170. class MultiNGram extends Transformer with HasInputCol with HasOutputCol with Wrappable with DefaultParamsWritable

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    Extracts several ngrams

  171. class MultiVectorAssembler extends VectorAssembler

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  172. class NER extends TextAnalyticsBase

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  173. case class NEREntity(value: String, startIndex: Int, precision: Double, category: String) extends Product with Serializable

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  174. case class NERScore(id: String, entities: Seq[NEREntity]) extends Product with Serializable

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  175. class NativeLoader extends Serializable

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  176. case class NetworkParams(executorIdToHost: Map[Int, String], defaultListenPort: Int, addr: String, port: Int) extends Product with Serializable

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  177. class NullOrdering[T] extends Ordering[T]

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  178. class OCR extends CognitiveServicesBase with HasLanguage with HasImageUrl with HasDetectOrientation with HasCognitiveServiceInput with HasInternalJsonOutputParser

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  179. class PageSplitter extends Transformer with HasInputCol with HasOutputCol with Wrappable with DefaultParamsWritable

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    Splits text into chunks of at most n characters

  180. class PartitionConsolidator extends Transformer with HTTPParams with HasInputCol with HasOutputCol with ComplexParamsWritable

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  181. sealed class PartitionSample extends Transformer with PartitionSampleParams

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  182. trait PartitionSampleParams extends Wrappable with DefaultParamsWritable

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  183. case class ProtocolVersionData(protocol: String, major: Int, minor: Int) extends Product with Serializable

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  184. class RandomDatasetGenerationConstraints extends HasDatasetGenerationConstraints

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    Contraints on generating a dataset where all parameters are randomly generated.

  185. abstract class RandomMMLGenerator[T] extends RandomDataGenerator[T]

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    Base abstract class for random generation of data.

    Base abstract class for random generation of data.

    T

    The data to generate.

  186. class RandomRowGenerator extends RandomMMLGenerator[Row]

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    Randomly generates a row given the set space of data, column options.

  187. class RandomRowGeneratorCombiner extends RandomMMLGenerator[Row]

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    Combines an array of row generators into a single row generator.

  188. class RandomSpace extends ParamSpace

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    Represents a generator of parameters with specified distributions added by the HyperparamBuilder.

  189. abstract class RangeHyperParam[T] extends Dist[T]

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  190. class RecognizeDomainSpecificContent extends CognitiveServicesBase with HasImageUrl with HasServiceParams with HasCognitiveServiceInput with HasInternalJsonOutputParser

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  191. class RecognizeText extends CognitiveServicesBaseWithoutHandler with HasImageUrl with HasCognitiveServiceInput with HasInternalJsonOutputParser

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  192. case class RegressorTrainParams(parallelism: String, numIterations: Int, learningRate: Double, numLeaves: Int, objective: String, alpha: Double, tweedieVariancePower: Double, maxBin: Int, baggingFraction: Double, baggingFreq: Int, baggingSeed: Int, earlyStoppingRound: Int, featureFraction: Double, maxDepth: Int, minSumHessianInLeaf: Double, numMachines: Int, modelString: String) extends TrainParams with Product with Serializable

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    Defines the Booster parameters passed to the LightGBM regressor.

  193. class RenameColumn extends Transformer with Wrappable with DefaultParamsWritable with HasInputCol with HasOutputCol

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    RenameColumn takes a dataframe with an input and an output column name and returns a dataframe comprised of the original columns with the input column renamed as the output column name.

    RenameColumn takes a dataframe with an input and an output column name and returns a dataframe comprised of the original columns with the input column renamed as the output column name.

  194. class Repartition extends Transformer with Wrappable with DefaultParamsWritable

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    Partitions the dataset into n partitions

  195. case class RequestLineData(method: String, uri: String, protoclVersion: Option[ProtocolVersionData]) extends Product with Serializable

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  196. class ResizeImage extends ImageTransformerStage

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    Resizes the image.

    Resizes the image. The parameters of the ParameterMap are: "height" - the height of the image "width" "stageName" Please refer to OpenCV for more information

  197. class ResizeImageTransformer extends Transformer with HasInputCol with HasOutputCol with Wrappable with DefaultParamsWritable

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    Annotations
    @InternalWrapper()
  198. abstract class Schema extends AnyRef

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    Abstract representation of a schema for an item that can be held in a repository

  199. class SelectColumns extends Transformer with Wrappable with DefaultParamsWritable

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    SelectColumns takes a dataframe and a list of columns to select as input and returns a dataframe comprised of only those columns listed in the input list.

    SelectColumns takes a dataframe and a list of columns to select as input and returns a dataframe comprised of only those columns listed in the input list.

    The columns to be selected is a list of column names

  200. case class SentimentScore(id: String, score: Float) extends Product with Serializable

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  201. class SharedSingleton[T] extends Serializable

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    Holds a variable shared among all workers that behaves like a local singleton.

    Holds a variable shared among all workers that behaves like a local singleton. Useful to use non-serializable objects in Spark closures that maintain state across tasks.

  202. class SharedVariable[T] extends Serializable

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    Holds a variable shared among all workers.

    Holds a variable shared among all workers. Useful to use non-serializable objects in Spark closures.

    Note this code has been borrowed from: https://www.nicolaferraro.me/2016/02/22/using-non-serializable-objects-in-apache-spark/

  203. class SimpleHTTPTransformer extends Transformer with HTTPParams with HasMiniBatcher with HasHandler with HasInputCol with HasOutputCol with ComplexParamsWritable with HasErrorCol

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  204. abstract class SingleFileResolver extends DataWriter

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  205. class SingleThreadedHTTPClient extends HTTPClient with SingleThreadedClient

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  206. abstract class SingleTypeReducer extends Transformer with TypeConversion

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  207. class SingleVectorAssembler extends VectorAssembler

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  208. case class StatusLineData(protocolVersion: ProtocolVersionData, statusCode: Int, reasonPhrase: String) extends Product with Serializable

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  209. class SummarizeData extends Transformer with SummarizeDataParams

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    Compute summary statistics for the dataset.

    Compute summary statistics for the dataset. The following statistics are computed: - counts - basic - sample - percentiles - errorThreshold - error threshold for quantiles

  210. trait SummarizeDataParams extends Wrappable with DefaultParamsWritable

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  211. class Superpixel extends org.apache.spark.internal.Logging

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  212. case class SuperpixelData(clusters: Seq[Seq[(Int, Int)]]) extends Product with Serializable

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  213. class SuperpixelTransformer extends Transformer with HasInputCol with HasOutputCol with Wrappable with DefaultParamsWritable with HasCellSize with HasModifier

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    A transformer that decomposes an image into it's superpixels

  214. case class TADocument(language: Option[String], id: String, text: String) extends Product with Serializable

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  215. case class TAError(id: String, message: String) extends Product with Serializable

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  216. case class TARequest(documents: Seq[TADocument]) extends Product with Serializable

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  217. case class TAResponse[T](documents: Seq[T], errors: Option[Seq[TAError]]) extends Product with Serializable

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  218. class TLCConfig extends MMLConfig

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  219. abstract class TestBase extends FunSuite with BeforeAndAfterEachTestData with BeforeAndAfterAll

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  220. abstract class TextAnalyticsBase extends CognitiveServicesBase with HasCognitiveServiceInput with HasInternalJsonOutputParser

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  221. class TextFeaturizer extends Estimator[TextFeaturizerModel] with TextFeaturizerParams with HasInputCol with HasOutputCol

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    Featurize text.

  222. class TextFeaturizerModel extends Model[TextFeaturizerModel] with ConstructorWritable[TextFeaturizerModel]

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  223. trait TextFeaturizerParams extends Wrappable with DefaultParamsWritable

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  224. class TextPreprocessor extends Transformer with HasInputCol with HasOutputCol with Wrappable with ComplexParamsWritable

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    TextPreprocessor takes a dataframe and a dictionary that maps (text -> replacement text), scans each cell in the input col and replaces all substring matches with the corresponding value.

    TextPreprocessor takes a dataframe and a dictionary that maps (text -> replacement text), scans each cell in the input col and replaces all substring matches with the corresponding value. Priority is given to longer keys and from left to right.

  225. class TextSentiment extends TextAnalyticsBase

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  226. class Threshold extends ImageTransformerStage

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    Applies a threshold to each element of the image.

    Applies a threshold to each element of the image. Please refer to threshold for more information

  227. class TimeIntervalBatcher[T] extends Iterator[List[T]]

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  228. class TimeIntervalMiniBatchTransformer extends Transformer with MiniBatchBase

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  229. class Timer extends Estimator[TimerModel] with TimerParams with ComplexParamsWritable

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  230. class TimerModel extends Model[TimerModel] with TimerParams with ConstructorWritable[TimerModel]

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  231. trait TimerParams extends Wrappable

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  232. class TrainClassifier extends Estimator[TrainedClassifierModel] with HasLabelCol with ComplexParamsWritable with HasFeaturesCol

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    Trains a classification model.

    Trains a classification model. Featurizes the given data into a vector of doubles.

    Note the behavior of the reindex and labels parameters, the parameters interact as:

    reindex -> false labels -> false (Empty) Assume all double values, don't use metadata, assume natural ordering

    reindex -> true labels -> false (Empty) Index, use natural ordering of string indexer

    reindex -> false labels -> true (Specified) Assume user knows indexing, apply label values. Currently only string type supported.

    reindex -> true labels -> true (Specified) Validate labels matches column type, try to recast to label type, reindex label column

  233. abstract class TrainParams extends Serializable

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    Defines the common Booster parameters passed to the LightGBM learners.

  234. class TrainRegressor extends Estimator[TrainedRegressorModel] with HasLabelCol with Wrappable with ComplexParamsWritable

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    Trains a regression model.

  235. class TrainedClassifierModel extends Model[TrainedClassifierModel] with ConstructorWritable[TrainedClassifierModel]

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    Model produced by TrainClassifier.

  236. class TrainedRegressorModel extends Model[TrainedRegressorModel] with ConstructorWritable[TrainedRegressorModel]

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    Model produced by TrainRegressor.

  237. class Trie extends Serializable

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  238. class TuneHyperparameters extends Estimator[TuneHyperparametersModel] with Wrappable with ComplexParamsWritable with HasEvaluationMetric

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    Tunes model hyperparameters

    Tunes model hyperparameters

    Allows user to specify multiple untrained models to tune using various search strategies. Currently supports cross validation with random grid search.

    Annotations
    @InternalWrapper()
  239. class TuneHyperparametersModel extends Model[TuneHyperparametersModel] with ConstructorWritable[TuneHyperparametersModel]

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    Model produced by TuneHyperparameters.

    Model produced by TuneHyperparameters.

    Annotations
    @InternalWrapper()
  240. trait TypeConversion extends AnyRef

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  241. class UDFTransformer extends Transformer with Wrappable with ComplexParamsWritable with HasInputCol with HasInputCols with HasOutputCol

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    UDFTransformer takes as input input column, output column, and a UserDefinedFunction returns a dataframe comprised of the original columns with the output column as the result of the udf applied to the input column

    UDFTransformer takes as input input column, output column, and a UserDefinedFunction returns a dataframe comprised of the original columns with the output column as the result of the udf applied to the input column

    Annotations
    @InternalWrapper()
  242. class UnrollBinaryImage extends Transformer with HasInputCol with HasOutputCol with Wrappable with DefaultParamsWritable

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    Converts the representation of an m X n pixel image to an m * n vector of Doubles

    Converts the representation of an m X n pixel image to an m * n vector of Doubles

    The input column name is assumed to be "image", the output column name is "<uid>_output"

  243. class UnrollImage extends Transformer with HasInputCol with HasOutputCol with Wrappable with DefaultParamsWritable

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    Converts the representation of an m X n pixel image to an m * n vector of Doubles

    Converts the representation of an m X n pixel image to an m * n vector of Doubles

    The input column name is assumed to be "image", the output column name is "<uid>_output"

  244. class ValueIndexer extends Estimator[ValueIndexerModel] with ValueIndexerParams

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    Fits a dictionary of values from the input column.

    Fits a dictionary of values from the input column. Model then transforms a column to a categorical column of the given array of values. Similar to StringIndexer except it can be used on any value types.

  245. class ValueIndexerModel extends Model[ValueIndexerModel] with ValueIndexerParams with ComplexParamsWritable

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    Model produced by ValueIndexer.

  246. trait ValueIndexerParams extends Wrappable with DefaultParamsWritable with HasInputCol with HasOutputCol

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  247. abstract class VectorAssembler extends AnyRef

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  248. class VerifyFaces extends CognitiveServicesBase with HasServiceParams with HasCognitiveServiceInput with HasInternalJsonOutputParser

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  249. trait Wrappable extends Params

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Value Members

  1. object AnalyzeImage extends ComplexParamsReadable[AnalyzeImage] with Serializable

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  2. object AssembleFeatures extends DefaultParamsReadable[AssembleFeatures] with Serializable

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  3. object AssembleFeaturesModel extends ConstructorReadable[AssembleFeaturesModel] with Serializable

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  4. object AsyncUtils

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  5. object Benchmark extends Serializable

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  6. object BestModel extends ConstructorReadable[BestModel] with Serializable

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  7. object Binary

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    Implicit conversion allows sparkSession.readImages(...) syntax Example: import com.microsoft.ml.spark.Readers.implicits._ sparkSession.readImages(path, recursive = false)

  8. object BinaryFileReader

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  9. object BingImage extends SparkBindings[BingImage]

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  10. object BingImageSearch extends ComplexParamsReadable[BingImageSearch] with Serializable

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  11. object BingImagesResponse extends SparkBindings[BingImagesResponse]

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  12. object Blur extends Serializable

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  13. object CNTKLearner extends DefaultParamsReadable[CNTKLearner] with Serializable

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  14. object CNTKModel extends ComplexParamsReadable[CNTKModel] with Serializable

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  15. object Cacher extends DefaultParamsReadable[Cacher] with Serializable

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  16. object CastUtilities

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    Utilities for casting values.

  17. object CheckpointData extends DefaultParamsReadable[CheckpointData] with Serializable

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    Cache the dataset to memory or memory and disk.

  18. object ClassBalancer extends DefaultParamsReadable[ClassBalancer] with Serializable

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  19. object ClassBalancerModel extends ConstructorReadable[ClassBalancerModel] with Serializable

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  20. object CleanMissingData extends DefaultParamsReadable[CleanMissingData] with Serializable

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  21. object CleanMissingDataModel extends ConstructorReadable[CleanMissingDataModel] with Serializable

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  22. object CognitiveServiceUtils

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  23. object ColorFormat extends Serializable

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  24. object ColumnOptions extends Enumeration

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    Specifies the column types supported in spark dataframes and modules.

  25. object ComputeModelStatistics extends DefaultParamsReadable[ComputeModelStatistics] with Serializable

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  26. object ComputePerInstanceStatistics extends DefaultParamsReadable[ComputePerInstanceStatistics] with Serializable

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  27. object ConversionUtils

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  28. object CropImage extends Serializable

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  29. object CustomInputParser extends ComplexParamsReadable[CustomInputParser] with Serializable

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  30. object CustomOutputParser extends ComplexParamsReadable[CustomOutputParser] with Serializable

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  31. object DataConversion extends DefaultParamsReadable[DataConversion] with Serializable

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    DataConversion object.

  32. object DataOptions extends Enumeration

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    Specifies the data types supported in spark dataframes and modules.

  33. object DataTransferUtils

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    Utilities for reducing data to CNTK format and generating the text file output to disk.

  34. object DatasetOptions extends Serializable

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  35. object DatasetUtils

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  36. object DefaultHyperparams

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    Provides good default hyperparameter ranges and values for sweeping.

    Provides good default hyperparameter ranges and values for sweeping. Publicly visible to users so they can easily select the parameters for sweeping.

  37. object DetectEntitiesResponse extends SparkBindings[TAResponse[DetectEntitiesScore]]

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  38. object DetectFace extends ComplexParamsReadable[DetectFace] with Serializable

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  39. object DetectLanguageResponse extends SparkBindings[TAResponse[DetectLanguageScore]]

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  40. object DropColumns extends DefaultParamsReadable[DropColumns] with Serializable

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  41. object DynamicMiniBatchTransformer extends DefaultParamsReadable[DynamicMiniBatchTransformer] with Serializable

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  42. object EnsembleByKey extends DefaultParamsReadable[EnsembleByKey] with Serializable

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  43. object EntityData extends SparkBindings[EntityData]

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  44. object EntityDetector extends ComplexParamsReadable[EntityDetector] with Serializable

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  45. object EnvironmentUtils

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  46. object ErrorUtils extends Serializable

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  47. object EvaluationUtils

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  48. object Explode extends DefaultParamsReadable[Explode] with Serializable

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  49. object FaceList

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  50. object FaceListProtocol

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  51. object FaceUtils

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  52. object FaultToleranceUtils

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  53. object Featurize extends DefaultParamsReadable[Featurize] with Serializable

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  54. object FileUtilities

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  55. object FindBestModel extends ComplexParamsReadable[FindBestModel] with Serializable

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  56. object FindSimilarFace extends ComplexParamsReadable[FindSimilarFace] with Serializable

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  57. object FixedMiniBatchTransformer extends DefaultParamsReadable[FixedMiniBatchTransformer] with Serializable

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  58. object FlattenBatch extends DefaultParamsReadable[FlattenBatch] with Serializable

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  59. object Flip extends Serializable

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  60. object FluentAPI

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  61. object GaussianKernel extends Serializable

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  62. object GenerateDataset

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    Defines methods to generate a random spark DataFrame dataset based on given options.

  63. object GenerateThumbnails extends ComplexParamsReadable[GenerateThumbnails] with Serializable

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  64. object GroupFaces extends ComplexParamsReadable[GroupFaces] with Serializable

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  65. object HTTPRequestData extends SparkBindings[HTTPRequestData]

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  66. object HTTPResponseData extends SparkBindings[HTTPResponseData]

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  67. object HTTPSchema

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  68. object HTTPTransformer extends ComplexParamsReadable[HTTPTransformer] with Serializable

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  69. object HandlingUtils extends org.apache.spark.internal.Logging

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  70. object HeaderData extends SparkBindings[HeaderData]

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  71. object HyperParamUtils

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  72. object IdentifyFaces extends ComplexParamsReadable[IdentifyFaces] with Serializable

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  73. object Image

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    Implicit conversion allows sparkSession.readImages(...) syntax Example: import com.microsoft.ml.spark.Readers.implicits._ sparkSession.readImages(path, recursive = false)

  74. object ImageFeaturizer extends ComplexParamsReadable[ImageFeaturizer] with Serializable

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  75. object ImageLIME extends ComplexParamsReadable[ImageLIME] with Serializable

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  76. object ImageReader

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  77. object ImageSetAugmenter extends DefaultParamsReadable[ImageSetAugmenter] with Serializable

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  78. object ImageTransformer extends DefaultParamsReadable[ImageTransformer] with Serializable

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    Pipelined image processing.

  79. object ImageWriter

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  80. object IndexToValue extends DefaultParamsReadable[IndexToValue] with Serializable

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  81. object JSONInputParser extends ComplexParamsReadable[JSONInputParser] with Serializable

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  82. object JSONOutputParser extends ComplexParamsReadable[JSONOutputParser] with Serializable

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  83. object JarLoadingUtils

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    Contains logic for loading classes.

  84. object KeyPhraseExtractor extends ComplexParamsReadable[EntityDetector] with Serializable

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  85. object KeyPhraseResponse extends SparkBindings[TAResponse[KeyPhraseScore]]

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  86. object Lambda extends ComplexParamsReadable[Lambda] with Serializable

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  87. object LanguageDetector extends ComplexParamsReadable[LanguageDetector] with Serializable

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  88. object LightGBMClassificationModel extends ConstructorReadable[LightGBMClassificationModel] with Serializable

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  89. object LightGBMClassifier extends DefaultParamsReadable[LightGBMClassifier] with Serializable

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  90. object LightGBMConstants

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  91. object LightGBMRegressionModel extends ConstructorReadable[LightGBMRegressionModel] with Serializable

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  92. object LightGBMRegressor extends DefaultParamsReadable[LightGBMRegressor] with Serializable

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  93. object LightGBMUtils

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    Helper utilities for LightGBM learners

  94. object Logging

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  95. object MMLConfig

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  96. object MultiColumnAdapter extends ComplexParamsReadable[MultiColumnAdapter] with Serializable

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  97. object MultiNGram extends DefaultParamsReadable[MultiNGram] with Serializable

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  98. object MultiVectorAssembler

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  99. object NER extends ComplexParamsReadable[NER] with Serializable

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  100. object NERResponse extends SparkBindings[TAResponse[NERScore]]

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  101. object NullOrdering extends Serializable

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  102. object OCR extends ComplexParamsReadable[OCR] with Serializable

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  103. object PSConstants

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    Constants for PartitionSample.

    Constants for PartitionSample.

  104. object PageSplitter extends DefaultParamsReadable[PageSplitter] with Serializable

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  105. object PartitionConsolidator extends DefaultParamsReadable[PartitionConsolidator] with Serializable

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  106. object PartitionSample extends DefaultParamsReadable[PartitionSample] with Serializable

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  107. object Person

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  108. object PersonGroup

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  109. object PersonGroupProtocol

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  110. object PersonProtocol

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  111. object PortForwarding

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  112. object PowerBIWriter

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  113. object ProcessUtils

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  114. object ProtocolVersionData extends SparkBindings[ProtocolVersionData]

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  115. object Readers

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    Implicit conversion allows sparkSession.readImages(...) syntax Example: import com.microsoft.ml.spark.Readers.implicits._ sparkSession.readImages(path, recursive = false)

  116. object RecognizeDomainSpecificContent extends ComplexParamsReadable[RecognizeDomainSpecificContent] with Serializable

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  117. object RecognizeText extends ComplexParamsReadable[RecognizeText] with Serializable

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  118. object RenameColumn extends DefaultParamsReadable[RenameColumn] with Serializable

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  119. object Repartition extends DefaultParamsReadable[Repartition] with Serializable

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  120. object RequestLineData extends SparkBindings[RequestLineData]

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  121. object ResizeImage extends Serializable

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    Resize object contains the information for resizing; "height" "width" "stageName" = "resize"

  122. object ResizeImageTransformer extends DefaultParamsReadable[ResizeImageTransformer] with Serializable

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  123. object ResizeUtils

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  124. object SelectColumns extends DefaultParamsReadable[SelectColumns] with Serializable

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  125. object SentimentResponse extends SparkBindings[TAResponse[SentimentScore]]

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  126. object ServingImplicits

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  127. object SharedSingleton extends Serializable

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  128. object SharedVariable extends Serializable

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  129. object SimpleHTTPTransformer extends ComplexParamsReadable[SimpleHTTPTransformer] with Serializable

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  130. object SparkSessionFactory

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  131. object StatusLineData extends SparkBindings[StatusLineData]

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  132. object StreamUtilities

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  133. object SummarizeData extends DefaultParamsReadable[SummarizeData] with Serializable

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  134. object Superpixel

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    Based on "Superpixel algorithm implemented in Java" at popscan.blogspot.com/2014/12/superpixel-algorithm-implemented-in-java.html

  135. object SuperpixelData extends Serializable

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  136. object SuperpixelTransformer extends DefaultParamsReadable[SuperpixelTransformer] with Serializable

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  137. object TADocument extends SparkBindings[TADocument]

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  138. object TAError extends SparkBindings[TAError]

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  139. object TAJSONFormat

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  140. object TARequest extends SparkBindings[TARequest]

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  141. object TestBase extends Serializable

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  142. object TextAnalyticsUtils extends Serializable

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  143. object TextFeaturizer extends DefaultParamsReadable[TextFeaturizer] with Serializable

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  144. object TextFeaturizerModel extends ConstructorReadable[TextFeaturizerModel] with Serializable

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  145. object TextPreprocessor extends ComplexParamsReadable[TextPreprocessor] with Serializable

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  146. object TextSentiment extends ComplexParamsReadable[TextSentiment] with Serializable

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  147. object Threshold extends Serializable

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  148. object TimeIntervalMiniBatchTransformer extends DefaultParamsReadable[TimeIntervalMiniBatchTransformer] with Serializable

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  149. object Timer extends ComplexParamsReadable[Timer] with Serializable

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  150. object TimerModel extends ConstructorReadable[TimerModel] with Serializable

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  151. object TrainClassifier extends ComplexParamsReadable[TrainClassifier] with Serializable

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  152. object TrainRegressor extends ComplexParamsReadable[TrainRegressor] with Serializable

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  153. object TrainedClassifierModel extends ConstructorReadable[TrainedClassifierModel] with Serializable

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  154. object TrainedRegressorModel extends ConstructorReadable[TrainedRegressorModel] with Serializable

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  155. object Trie extends Serializable

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  156. object TuneHyperparameters extends ComplexParamsReadable[TuneHyperparameters] with Serializable

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  157. object TuneHyperparametersModel extends ConstructorReadable[TuneHyperparametersModel] with Serializable

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  158. object TypeMapping

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  159. object UDFTransformer extends ComplexParamsReadable[UDFTransformer] with Serializable

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  160. object URLEncodingUtils

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  161. object UnrollBinaryImage extends DefaultParamsReadable[UnrollBinaryImage] with Serializable

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  162. object UnrollImage extends DefaultParamsReadable[UnrollImage] with Serializable

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  163. object ValueIndexer extends DefaultParamsReadable[ValueIndexer] with Serializable

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  164. object ValueIndexerModel extends ComplexParamsReadable[ValueIndexerModel] with Serializable

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  165. object VerifyFaces extends ComplexParamsReadable[VerifyFaces] with Serializable

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  166. package codegen

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  167. package cognitive

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  168. package contracts

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  169. package hadoop

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  170. package metrics

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  171. package schema

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  172. object udfs

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Inherited from AnyRef

Inherited from Any

Members