PySpark API Supportability Matrix | LinearSVC Function | pyspark2teradataml - LinearSVC - 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
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oeg1710443196055.ditamap
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ayr1485454803741.ditaval
dita:id
oeg1710443196055
Product Category
Teradata Vantage

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

Transformed DataFrame do not have features and rawPrediction columns. See Examples for more details.

Arguments

teradatamlspk Argument Name Optional Source Function Argument Name Notes
maxIter max_iter  
tol tol  
fitIntercept fit_intercept  
regParam C teradatamlspk supports int value (>1).

Default value is 1.0.

weightCol classic_weight  
standardization Not yet available  
threshold Not yet available  
aggregationDepth Not yet available  

Attributes/Methods

Attribute/Method Name Supported Notes
clear  
copy  
explainParam  
explainParams  
extractParamMap  
fit  
fitMultiple  
getAggregationDepth  
getFeaturesCol  
getFitIntercept  
getLabelCol  
getMaxBlockSizeInMB  
getMaxIter  
getOrDefault  
getParam  
getPredictionCol  
getRawPrediction  
getRawPredictionCol  
getRegParam  
getStandardization  
getThreshold  
getTol  
getWeightCol  
hasDefault  
hasParam  
isDefined  
isSet  
load  
read  
save  
set  
setAggregationDepth  
setFeaturesCol  
setFitIntercept  
setLabelCol  
setMaxBlockSizeInMB  
setMaxIter  
setParams  
setStandardization  
setThreshold  
setTol  
setWeightCol  
write  
aggregationDepth  
featuresCol  
fitIntercept  
labelCol  
maxBlockSizeInMB  
maxIter  
params  
predictionCol  
rawPredictionCol  
regParam  
standardization  
threshold  
tol  
weightCol