bigdl.models.ml_pipeline package

Submodules

bigdl.models.ml_pipeline.dl_classifier module

class bigdl.models.ml_pipeline.dl_classifier.DLClassifier(model, criterion, feature_size, bigdl_type='float')

Bases: bigdl.models.ml_pipeline.dl_classifier.DLEstimator

class bigdl.models.ml_pipeline.dl_classifier.DLClassifierModel(model, featureSize, jvalue=None, bigdl_type='float')

Bases: bigdl.models.ml_pipeline.dl_classifier.DLModel

classmethod of(jvalue, feature_size=None, bigdl_type='float')

class bigdl.models.ml_pipeline.dl_classifier.DLEstimator(model, criterion, feature_size, label_size, jvalue=None, bigdl_type='float')

Bases: pyspark.ml.pipeline.Estimator, pyspark.ml.param.shared.HasFeaturesCol, pyspark.ml.param.shared.HasLabelCol, pyspark.ml.param.shared.HasPredictionCol, bigdl.models.ml_pipeline.dl_classifier.HasBatchSize, bigdl.models.ml_pipeline.dl_classifier.HasMaxEpoch, bigdl.models.ml_pipeline.dl_classifier.HasLearningRate, bigdl.util.common.JavaValue

class bigdl.models.ml_pipeline.dl_classifier.DLModel(model, featureSize, jvalue=None, bigdl_type='float')

Bases: pyspark.ml.pipeline.Model, pyspark.ml.param.shared.HasFeaturesCol, pyspark.ml.param.shared.HasPredictionCol, bigdl.models.ml_pipeline.dl_classifier.HasBatchSize, bigdl.models.ml_pipeline.dl_classifier.HasFeatureSize, bigdl.util.common.JavaValue

classmethod of(jvalue, feature_size=None, bigdl_type='float')

class bigdl.models.ml_pipeline.dl_classifier.HasBatchSize

Bases: pyspark.ml.param.Params

Mixin for param batchSize: batch size.

batchSize = Param(parent='undefined', name='batchSize', doc='batchSize')

param for batch size.

getBatchSize()

Gets the value of batchSize or its default value.

setBatchSize(val)

Sets the value of batchSize.

class bigdl.models.ml_pipeline.dl_classifier.HasFeatureSize

Bases: pyspark.ml.param.Params

featureSize = Param(parent='undefined', name='featureSize', doc='size of the feature')

getFeatureSize()

setFeatureSize(val)

class bigdl.models.ml_pipeline.dl_classifier.HasLearningRate

Bases: pyspark.ml.param.Params

getLearningRate()

Gets the value of maxEpoch or its default value.

learningRate = Param(parent='undefined', name='learningRate', doc='learning rate')

setLearningRate(val)

class bigdl.models.ml_pipeline.dl_classifier.HasMaxEpoch

Bases: pyspark.ml.param.Params

getMaxEpoch()

Gets the value of maxEpoch or its default value.

maxEpoch = Param(parent='undefined', name='maxEpoch', doc='number of max Epoch')

setMaxEpoch(val)

Module contents