PySpark API Supportability Matrix | GBTClassifier | pyspark2teradataml - GBTClassifier - Teradata Package for Python

Teradata® pyspark2teradataml User Guide

Deployment
VantageCloud
VantageCore
Edition
Enterprise
IntelliFlex
VMware
Product
Teradata Package for Python
Release Number
20.00
Published
December 2024
ft:locale
en-US
ft:lastEdition
2024-12-18
dita:mapPath
oeg1710443196055.ditamap
dita:ditavalPath
ayr1485454803741.ditaval
dita:id
oeg1710443196055
Product Category
Teradata Vantage

Arguments

This function internally uses scikit-learn function GradientBoostingClassifier through teradataml Open source ML functions.

Transformed data won’t have features, rawPrediction, probability columns.

PySpark Argument Name Open Source Function Argument Name Notes
predictionCol Not yet available.  
maxDepth max_depth  
maxBins Not yet available.  
minInstancesPerNode min_samples_split PySpark takes int value (>= 1) default value is 1, teradatamlspk supports int value (>1) or float in (0.0, 1.0].

Default value is 1.0.

minInfoGain Not yet available.  
maxMemoryInMB Not yet available.  
cacheNodeIds Not yet available.  
checkpointInterval Not yet available.  
lossType loss Supported values ['deviance', 'exponential'].
maxIter Not yet available.  
stepSize learning_rate  
seed random_state  
subsamplingRate subsample  
impurity criterion Supported values ['friedman_mse','mse','mae']
featureSubsetStrategy Not yet available.  
validationTol Not yet available.  
validationIndicatorCol Not yet available.  
leafCol Not yet available.  
minWeightFractionPerNode min_weight_fraction_leaf  
weightCol Not yet available.  

Attributes/Methods

Attribute/Method Name Supported Notes
clear  
copy  
explainParam  
explainParams  
extractParamMap  
fit  
fitMultiple  
getCacheNodeIds  
getCheckpointInterval  
getFeatureSubsetStrategy  
getFeaturesCol  
getImpurity  
getLabelCol  
getLeafCol  
getLossType  
getMaxBins  
getMaxDepth  
getMaxIter  
getMaxMemoryInMB  
getMinInfoGain  
getMinInstancesPerNode  
getMinWeightFractionPerNode  
getOrDefault  
getParam  
getPredictionCol  
getProbabilityCol  
getRawPredictionCol  
getSeed  
getStepSize  
getSubsamplingRate  
getThresholds  
getValidationIndicatorCol  
getValidationTol  
getWeightCol  
hasDefault  
hasParam  
isDefined  
isSet  
load  
read  
save  
set  
setCacheNodeIds  
setCheckpointInterval  
setFeatureSubsetStrategy  
setFeaturesCol  
setImpurity  
setLabelCol  
setLeafCol  
setLossType  
setMaxBins  
setMaxDepth  
setMaxIter  
setMaxMemoryInMB  
setMinInfoGain  
setMinInstancesPerNode  
setMinWeightFractionPerNode  
setParams  
setPredictionCol  
setProbabilityCol  
setRawPredictionCol  
setSeed  
setStepSize  
setSubSamplingRate  
setThresholds  
setValidationIndicatorCol  
setWeightCol  
write  
cacheNodeIds  
checkpointInterval  
featureSubsetStrategy  
featuresCol  
impurity  
labelCol  
leafCol  
lossType  
maxBins  
maxDepth  
maxIter  
maxMemoryInMB  
minInfoGain  
minInstancesPerNode  
minWeightFractionPerNode  
params  
predictionCol  
probabilityCol  
rawPredictionCol  
seed  
stepSize  
subsamplingRate  
supportedFeatureSubsetStrategies  
supportedImpurities  
supportedLossTypes  
thresholds  
validationIndicatorCol  
validationTol  
weightCol