This function internally uses scikit-learn function LogisticRegression through teradataml Open source ML functions.
Attributes/Methods
Attribute/Method Name | Supported | Notes |
---|---|---|
clear | ||
copy | ||
evaluate | ||
explainParam | ||
explainParams | ||
extractParamMap | ||
getAggregationDepth | ||
getElasticNetParam | ||
getFamily | ||
getFeaturesCol | ||
getFitIntercept | ||
getLabelCol | ||
getLowerBoundsOnCoefficients | ||
getLowerBoundsOnIntercepts | ||
getMaxBlockSizeInMB | ||
getMaxIter | ||
getOrDefault | ||
getParam | ||
getPredictionCol | ||
get ProbabilityCol | ||
getRawPredictionCol | ||
getRegParam | ||
getStandardization | ||
getThreshold | ||
getThresholds | ||
getTol | ||
getUpperBoundsOnCoefficients | ||
getUpperBoundsOnIntercepts | ||
getWeightCol | ||
hasDefault | ||
hasParam | ||
isDefined | ||
isSet | ||
load | ||
predict | ||
predictProbability | ||
predictRaw | ||
read | ||
save | ||
set | ||
setFeaturesCol | ||
setPredictionCol | ||
setProbabilityCol | ||
setRawPredictionCol | ||
setThreshold | ||
setThresholds | ||
transform | ||
write | ||
aggregationDepth | ||
coefficientMatrix | ||
coefficients | ||
elasticNetParam | ||
family | ||
featuresCol | ||
fitIntercept | ||
hasSummary | ||
intercept | ||
interceptVector | ||
labelCol | ||
lowerBoundsOnCoefficients | ||
lowerBoundsOnIntercepts | ||
maxBlockSizeInMB | ||
maxIter | ||
numClasses | ||
numFeatures | ||
params | ||
predictionCol | ||
probabilityCol | ||
rawPredictionCol | ||
regParam | ||
standardization | ||
summary | ||
threshold | ||
thresholds | ||
tol | ||
upperBoundsOnCoefficients | ||
upperBoundsOnIntercepts | ||
weightCol |