PySpark API Supportability Matrix | KMeans Function | pyspark2teradataml - KMeans - 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 KMeans through teradataml Open source ML functions.

Transformed data won’t have the features column.

PySpark Argument Name Open Source Function Argument Name Notes
maxIter mater_iter  
k n_clusters  
initMode init Default value is k-means++.
initSteps n_init  
tol tol  
distanceMeasure Not yet available  
weightCol Not yet available  
solver Not yet available  
maxBlockSizeInMB Not yet available  

Attributes/Methods

Attribute/Method Name Supported Notes
clear  
copy  
explainParam  
explainParams  
extractParamMap  
fit  
fitMultiple  
getDistanceMeasure  
getFeaturesCol  
getInitMode  
getInitSteps  
getK  
getMaxBlockSizeInMB  
getMaxIter  
getOrDefault  
getParam  
getPredictionCol  
getSeed  
getSolver  
getTol  
getWeightCol  
hasDefault  
hasParam  
isDefined  
isSet  
load  
read  
save  
set  
setDistanceMeasure  
setFeaturesCol  
setInitMode  
setInitSteps  
setK  
setMaxBlockSizeInMB  
setMaxIter  
setParams  
setPredictionCol  
setSeed  
setSolver  
setTol  
setWeightCol  
write  
distanceMeasure  
featuresCol  
initMode  
initSteps  
k  
maxBlockSizeInMB  
maxIter  
params  
predictionCol  
seed  
solver  
tol  
weightCol