FeaturesType - Type of input features.  E.g., VectorM - Concrete Model typepublic abstract class ClassificationModel<FeaturesType,M extends ClassificationModel<FeaturesType,M>> extends PredictionModel<FeaturesType,M> implements ClassifierParams
 Model produced by a Classifier.
 Classes are indexed {0, 1, ..., numClasses - 1}.
 
| Constructor and Description | 
|---|
| ClassificationModel() | 
| Modifier and Type | Method and Description | 
|---|---|
| abstract int | numClasses()Number of classes (values which the label can take). | 
| double | predict(FeaturesType features)Predict label for the given features. | 
| M | setRawPredictionCol(String value) | 
| Dataset<Row> | transform(Dataset<?> dataset)Transforms dataset by reading from  featuresCol, and appending new columns as specified by
 parameters:
  - predicted labels aspredictionColof typeDouble- raw predictions (confidences) asrawPredictionColof typeVector. | 
numFeatures, setFeaturesCol, setPredictionCol, transformSchematransform, transform, transformequals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitvalidateAndTransformSchemagetLabelCol, labelColfeaturesCol, getFeaturesColgetPredictionCol, predictionColclear, copy, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwntoString, uidgetRawPredictionCol, rawPredictionColinitializeLogging, initializeLogIfNecessary, initializeLogIfNecessary, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarningpublic abstract int numClasses()
public double predict(FeaturesType features)
transform() and output predictionCol.
 
 This default implementation for classification predicts the index of the maximum value
 from predictRaw().
predict in class PredictionModel<FeaturesType,M extends ClassificationModel<FeaturesType,M>>features - (undocumented)public M setRawPredictionCol(String value)
public Dataset<Row> transform(Dataset<?> dataset)
featuresCol, and appending new columns as specified by
 parameters:
  - predicted labels as predictionCol of type Double
  - raw predictions (confidences) as rawPredictionCol of type Vector.
 transform in class PredictionModel<FeaturesType,M extends ClassificationModel<FeaturesType,M>>dataset - input dataset