ComputeModelStatistics

class ComputeModelStatistics.ComputeModelStatistics(evaluationMetric='all', labelCol=None, scoredLabelsCol=None, scoresCol=None)[source]

Bases: mmlspark.Utils.ComplexParamsMixin, pyspark.ml.util.JavaMLReadable, pyspark.ml.util.JavaMLWritable, pyspark.ml.wrapper.JavaTransformer

ComputeModelStatistics returns the specified statistics on all the models specified

The possible metrics are:

Binary Classifiers:

  • “AreaUnderROC”
  • “AUC”
  • “accuracy”
  • “recall”
  • “all”

Regression Classifiers:

  • “mse”
  • “rmse”
  • “r2”
  • “all”
Parameters:
  • evaluationMetric (str) – Metric to evaluate models with (default: all)
  • labelCol (str) – The name of the label column
  • scoredLabelsCol (str) – Scored labels column name, only required if using SparkML estimators
  • scoresCol (str) – Scores or raw prediction column name, only required if using SparkML estimators
getEvaluationMetric()[source]
Returns:Metric to evaluate models with (default: all)
Return type:str
static getJavaPackage()[source]

Returns package name String.

getLabelCol()[source]
Returns:The name of the label column
Return type:str
getScoredLabelsCol()[source]
Returns:Scored labels column name, only required if using SparkML estimators
Return type:str
getScoresCol()[source]
Returns:Scores or raw prediction column name, only required if using SparkML estimators
Return type:str
classmethod read()[source]

Returns an MLReader instance for this class.

setEvaluationMetric(value)[source]
Parameters:evaluationMetric (str) – Metric to evaluate models with (default: all)
setLabelCol(value)[source]
Parameters:labelCol (str) – The name of the label column
setParams(evaluationMetric='all', labelCol=None, scoredLabelsCol=None, scoresCol=None)[source]

Set the (keyword only) parameters

Parameters:
  • evaluationMetric (str) – Metric to evaluate models with (default: all)
  • labelCol (str) – The name of the label column
  • scoredLabelsCol (str) – Scored labels column name, only required if using SparkML estimators
  • scoresCol (str) – Scores or raw prediction column name, only required if using SparkML estimators
setScoredLabelsCol(value)[source]
Parameters:scoredLabelsCol (str) – Scored labels column name, only required if using SparkML estimators
setScoresCol(value)[source]
Parameters:scoresCol (str) – Scores or raw prediction column name, only required if using SparkML estimators