LightGBMClassifier¶
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class
LightGBMClassifier.
LightGBMClassificationModel
(java_model=None)[source]¶ Bases:
mmlspark._LightGBMClassifier._LightGBMClassificationModel
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getFeatureImportances
(importance_type='split')[source]¶ Get the feature importances as a list. The importance_type can be “split” or “gain”.
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static
loadNativeModelFromFile
(filename, labelColName='label', featuresColName='features', predictionColName='prediction', probColName='probability', rawPredictionColName='rawPrediction')[source]¶ Load the model from a native LightGBM text file.
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class
LightGBMClassifier.
LightGBMClassifier
(baggingFraction=1.0, baggingFreq=0, baggingSeed=3, boostFromAverage=True, boostingType='gbdt', categoricalSlotIndexes=None, categoricalSlotNames=None, defaultListenPort=12400, earlyStoppingRound=0, featureFraction=1.0, featuresCol='features', isUnbalance=False, labelCol='label', lambdaL1=0.0, lambdaL2=0.0, learningRate=0.1, maxBin=255, maxDepth=-1, minSumHessianInLeaf=0.001, modelString='', numIterations=100, numLeaves=31, objective='binary', parallelism='data_parallel', predictionCol='prediction', probabilityCol='probability', rawPredictionCol='rawPrediction', thresholds=None, timeout=1200.0, validationIndicatorCol=None, verbosity=1, weightCol=None)[source]¶ Bases:
mmlspark._LightGBMClassifier._LightGBMClassifier