This function internally uses scikit-learn function LogisticRegression through teradataml Open source ML functions.
LogisticRegressionModel will always return LogisticRegressionSummary object, irrespective of the number of classes.
Attributes/Methods
| Attribute/Method Name | Supported | Notes |
|---|---|---|
| fMeasureByLabel | ||
| weightedFMeasure | ||
| accuracy | ||
| areaUnderROC | ||
| fMeasureByThreshold | ||
| falsePositiveRateByLabel | ||
| featuresCol | ||
| labelCol | ||
| labels | ||
| pr | ||
| precisionByLabel | ||
| precisionByThreshold | ||
| predictionCol | ||
| predictions | ||
| probabilityCol | ||
| recallByLabel | ||
| recallByThreshold | ||
| roc | ||
| scoreCol | ||
| truePositiveRateByLabel | ||
| weightCol | ||
| weightedFalsePositiveRate | ||
| weightedPrecision | ||
| weightedRecall | ||
| weightedTruePositiveRate |