PySpark API Supportability Matrix | LinearRegressionModel | pyspark2teradataml - LinearRegressionModel - 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
dita:ditavalPath
ayr1485454803741.ditaval
dita:id
oeg1710443196055
Product Category
Teradata Vantage

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

Attributes/Methods

Attribute/Method Name Supported Notes
copy  
evaluate  
explainParam  
explainParams  
extractParamMap  
getAggregationDepth  
getElasticNetParam  
getEpsilon  
getFeaturesCol  
getFitIntercept  
getLabelCol  
getLoss  
getMaxBlockSizeInMB  
getMaxIter  
getOrDefault  
getParam  
getPredictionCol  
getRegParam  
getSolver  
getStandardization  
getThreshold  
getTol  
getWeightCol  
hasDefault  
hasParam  
isDefined  
isSet  
load  
predict  
read  
save  
set  
setFeaturesCol  
setPredictionCol  
transform  
write  
aggregationDepth  
coefficients PySpark returns a DenseVector, whereas teradatamlspk returns a numpy array.
elasticNetParam  
epsilon  
featuresCol  
fitIntercept  
hasSummary  
intercept  
labelCol  
loss  
maxBlockSizeInMB  
maxIter  
params  
predictionCol  
regParam  
scale  
solver  
standardization  
summary  
tol  
weightCol