public abstract class ClassificationModel<FeaturesType,M extends ClassificationModel<FeaturesType,M>> extends PredictionModel<FeaturesType,M>
Model produced by a Classifier
.
Classes are indexed {0, 1, ..., numClasses - 1}.
Constructor and Description |
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ClassificationModel() |
Modifier and Type | Method and Description |
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Param<String> |
featuresCol()
Param for features column name.
|
String |
getFeaturesCol() |
String |
getLabelCol() |
String |
getPredictionCol() |
String |
getRawPredictionCol() |
Param<String> |
labelCol()
Param for label column name.
|
abstract int |
numClasses()
Number of classes (values which the label can take).
|
Param<String> |
predictionCol()
Param for prediction column name.
|
Param<String> |
rawPredictionCol()
Param for raw prediction (a.k.a.
|
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 as predictionCol of type Double
- raw predictions (confidences) as rawPredictionCol of type Vector . |
StructType |
validateAndTransformSchema(StructType schema,
boolean fitting,
DataType featuresDataType) |
StructType |
validateAndTransformSchema(StructType schema,
boolean fitting,
DataType featuresDataType)
Validates and transforms the input schema with the provided param map.
|
numFeatures, setFeaturesCol, setPredictionCol, transformSchema
transform, transform, transform
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
clear, copy, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn, validateParams
toString, uid
public M setRawPredictionCol(String value)
public abstract int numClasses()
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 datasetpublic StructType validateAndTransformSchema(StructType schema, boolean fitting, DataType featuresDataType)
public Param<String> rawPredictionCol()
public String getRawPredictionCol()
public StructType validateAndTransformSchema(StructType schema, boolean fitting, DataType featuresDataType)
schema
- input schemafitting
- whether this is in fittingfeaturesDataType
- SQL DataType for FeaturesType.
E.g., VectorUDT
for vector features.public Param<String> labelCol()
public String getLabelCol()
public Param<String> featuresCol()
public String getFeaturesCol()
public Param<String> predictionCol()
public String getPredictionCol()