LinearSVCModel (Spark 3.5.5 JavaDoc) (original) (raw)

Object
- org.apache.spark.ml.PipelineStage
- - org.apache.spark.ml.Transformer
    - - org.apache.spark.ml.Model
        * * org.apache.spark.ml.PredictionModel<FeaturesType,M>
        * * org.apache.spark.ml.classification.ClassificationModel<Vector,LinearSVCModel>
        * * org.apache.spark.ml.classification.LinearSVCModel
All Implemented Interfaces:
java.io.Serializable, org.apache.spark.internal.Logging, ClassifierParams, LinearSVCParams, Params, HasAggregationDepth, HasFeaturesCol, HasFitIntercept, HasLabelCol, HasMaxBlockSizeInMB, HasMaxIter, HasPredictionCol, HasRawPredictionCol, HasRegParam, HasStandardization, HasThreshold, HasTol, HasWeightCol, PredictorParams, HasTrainingSummary<LinearSVCTrainingSummary>, Identifiable, MLWritable

public class LinearSVCModel
extends ClassificationModel<Vector,LinearSVCModel>
implements LinearSVCParams, MLWritable, HasTrainingSummary<LinearSVCTrainingSummary>
Linear SVM Model trained by LinearSVC
See Also:
Serialized Form

Nested Class Summary

 * ### Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging  
 `org.apache.spark.internal.Logging.SparkShellLoggingFilter`

Method Summary

All Methods Static Methods Instance Methods Concrete Methods

Modifier and Type	Method and Description
IntParam	aggregationDepth() Param for suggested depth for treeAggregate (>= 2).
Vector	coefficients()
LinearSVCModel	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
LinearSVCSummary	evaluate(Dataset<?> dataset) Evaluates the model on a test dataset.
BooleanParam	fitIntercept() Param for whether to fit an intercept term.
double	intercept()
static LinearSVCModel	load(String path)
DoubleParam	maxBlockSizeInMB() Param for Maximum memory in MB for stacking input data into blocks.
IntParam	maxIter() Param for maximum number of iterations (>= 0).
int	numClasses() Number of classes (values which the label can take).
int	numFeatures() Returns the number of features the model was trained on.
double	predict(Vector features) Predict label for the given features.
Vector	predictRaw(Vector features) Raw prediction for each possible label.
static MLReader<LinearSVCModel>	read()
DoubleParam	regParam() Param for regularization parameter (>= 0).
LinearSVCModel	setThreshold(double value)
BooleanParam	standardization() Param for whether to standardize the training features before fitting the model.
LinearSVCTrainingSummary	summary() Gets summary of model on training set.
DoubleParam	threshold() Param for threshold in binary classification prediction.
DoubleParam	tol() Param for the convergence tolerance for iterative algorithms (>= 0).
String	toString()
String	uid() An immutable unique ID for the object and its derivatives.
Param	weightCol() Param for weight column name.
MLWriter	write() Returns an MLWriter instance for this ML instance.

   * ### Methods inherited from class org.apache.spark.ml.classification.[ClassificationModel](../../../../../org/apache/spark/ml/classification/ClassificationModel.html "class in org.apache.spark.ml.classification")  
   `[rawPredictionCol](../../../../../org/apache/spark/ml/classification/ClassificationModel.html#rawPredictionCol--), [setRawPredictionCol](../../../../../org/apache/spark/ml/classification/ClassificationModel.html#setRawPredictionCol-java.lang.String-), [transform](../../../../../org/apache/spark/ml/classification/ClassificationModel.html#transform-org.apache.spark.sql.Dataset-), [transformImpl](../../../../../org/apache/spark/ml/classification/ClassificationModel.html#transformImpl-org.apache.spark.sql.Dataset-), [transformSchema](../../../../../org/apache/spark/ml/classification/ClassificationModel.html#transformSchema-org.apache.spark.sql.types.StructType-)`  
   * ### Methods inherited from class org.apache.spark.ml.[PredictionModel](../../../../../org/apache/spark/ml/PredictionModel.html "class in org.apache.spark.ml")  
   `[featuresCol](../../../../../org/apache/spark/ml/PredictionModel.html#featuresCol--), [labelCol](../../../../../org/apache/spark/ml/PredictionModel.html#labelCol--), [predictionCol](../../../../../org/apache/spark/ml/PredictionModel.html#predictionCol--), [setFeaturesCol](../../../../../org/apache/spark/ml/PredictionModel.html#setFeaturesCol-java.lang.String-), [setPredictionCol](../../../../../org/apache/spark/ml/PredictionModel.html#setPredictionCol-java.lang.String-)`  
   * ### Methods inherited from class org.apache.spark.ml.[Model](../../../../../org/apache/spark/ml/Model.html "class in org.apache.spark.ml")  
   `[hasParent](../../../../../org/apache/spark/ml/Model.html#hasParent--), [parent](../../../../../org/apache/spark/ml/Model.html#parent--), [setParent](../../../../../org/apache/spark/ml/Model.html#setParent-org.apache.spark.ml.Estimator-)`  
   * ### Methods inherited from class org.apache.spark.ml.[Transformer](../../../../../org/apache/spark/ml/Transformer.html "class in org.apache.spark.ml")  
   `[transform](../../../../../org/apache/spark/ml/Transformer.html#transform-org.apache.spark.sql.Dataset-org.apache.spark.ml.param.ParamMap-), [transform](../../../../../org/apache/spark/ml/Transformer.html#transform-org.apache.spark.sql.Dataset-org.apache.spark.ml.param.ParamPair-org.apache.spark.ml.param.ParamPair...-), [transform](../../../../../org/apache/spark/ml/Transformer.html#transform-org.apache.spark.sql.Dataset-org.apache.spark.ml.param.ParamPair-scala.collection.Seq-)`  
   * ### Methods inherited from class org.apache.spark.ml.[PipelineStage](../../../../../org/apache/spark/ml/PipelineStage.html "class in org.apache.spark.ml")  
   `[params](../../../../../org/apache/spark/ml/PipelineStage.html#params--)`  
   * ### Methods inherited from class Object  
   `equals, getClass, hashCode, notify, notifyAll, wait, wait, wait`  
   * ### Methods inherited from interface org.apache.spark.ml.classification.[ClassifierParams](../../../../../org/apache/spark/ml/classification/ClassifierParams.html "interface in org.apache.spark.ml.classification")  
   `[validateAndTransformSchema](../../../../../org/apache/spark/ml/classification/ClassifierParams.html#validateAndTransformSchema-org.apache.spark.sql.types.StructType-boolean-org.apache.spark.sql.types.DataType-)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasLabelCol](../../../../../org/apache/spark/ml/param/shared/HasLabelCol.html "interface in org.apache.spark.ml.param.shared")  
   `[getLabelCol](../../../../../org/apache/spark/ml/param/shared/HasLabelCol.html#getLabelCol--), [labelCol](../../../../../org/apache/spark/ml/param/shared/HasLabelCol.html#labelCol--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasFeaturesCol](../../../../../org/apache/spark/ml/param/shared/HasFeaturesCol.html "interface in org.apache.spark.ml.param.shared")  
   `[featuresCol](../../../../../org/apache/spark/ml/param/shared/HasFeaturesCol.html#featuresCol--), [getFeaturesCol](../../../../../org/apache/spark/ml/param/shared/HasFeaturesCol.html#getFeaturesCol--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasPredictionCol](../../../../../org/apache/spark/ml/param/shared/HasPredictionCol.html "interface in org.apache.spark.ml.param.shared")  
   `[getPredictionCol](../../../../../org/apache/spark/ml/param/shared/HasPredictionCol.html#getPredictionCol--), [predictionCol](../../../../../org/apache/spark/ml/param/shared/HasPredictionCol.html#predictionCol--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.[Params](../../../../../org/apache/spark/ml/param/Params.html "interface in org.apache.spark.ml.param")  
   `[clear](../../../../../org/apache/spark/ml/param/Params.html#clear-org.apache.spark.ml.param.Param-), [copyValues](../../../../../org/apache/spark/ml/param/Params.html#copyValues-T-org.apache.spark.ml.param.ParamMap-), [defaultCopy](../../../../../org/apache/spark/ml/param/Params.html#defaultCopy-org.apache.spark.ml.param.ParamMap-), [defaultParamMap](../../../../../org/apache/spark/ml/param/Params.html#defaultParamMap--), [explainParam](../../../../../org/apache/spark/ml/param/Params.html#explainParam-org.apache.spark.ml.param.Param-), [explainParams](../../../../../org/apache/spark/ml/param/Params.html#explainParams--), [extractParamMap](../../../../../org/apache/spark/ml/param/Params.html#extractParamMap--), [extractParamMap](../../../../../org/apache/spark/ml/param/Params.html#extractParamMap-org.apache.spark.ml.param.ParamMap-), [get](../../../../../org/apache/spark/ml/param/Params.html#get-org.apache.spark.ml.param.Param-), [getDefault](../../../../../org/apache/spark/ml/param/Params.html#getDefault-org.apache.spark.ml.param.Param-), [getOrDefault](../../../../../org/apache/spark/ml/param/Params.html#getOrDefault-org.apache.spark.ml.param.Param-), [getParam](../../../../../org/apache/spark/ml/param/Params.html#getParam-java.lang.String-), [hasDefault](../../../../../org/apache/spark/ml/param/Params.html#hasDefault-org.apache.spark.ml.param.Param-), [hasParam](../../../../../org/apache/spark/ml/param/Params.html#hasParam-java.lang.String-), [isDefined](../../../../../org/apache/spark/ml/param/Params.html#isDefined-org.apache.spark.ml.param.Param-), [isSet](../../../../../org/apache/spark/ml/param/Params.html#isSet-org.apache.spark.ml.param.Param-), [onParamChange](../../../../../org/apache/spark/ml/param/Params.html#onParamChange-org.apache.spark.ml.param.Param-), [paramMap](../../../../../org/apache/spark/ml/param/Params.html#paramMap--), [params](../../../../../org/apache/spark/ml/param/Params.html#params--), [set](../../../../../org/apache/spark/ml/param/Params.html#set-org.apache.spark.ml.param.Param-T-), [set](../../../../../org/apache/spark/ml/param/Params.html#set-org.apache.spark.ml.param.ParamPair-), [set](../../../../../org/apache/spark/ml/param/Params.html#set-java.lang.String-java.lang.Object-), [setDefault](../../../../../org/apache/spark/ml/param/Params.html#setDefault-org.apache.spark.ml.param.Param-T-), [setDefault](../../../../../org/apache/spark/ml/param/Params.html#setDefault-scala.collection.Seq-), [shouldOwn](../../../../../org/apache/spark/ml/param/Params.html#shouldOwn-org.apache.spark.ml.param.Param-)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasRawPredictionCol](../../../../../org/apache/spark/ml/param/shared/HasRawPredictionCol.html "interface in org.apache.spark.ml.param.shared")  
   `[getRawPredictionCol](../../../../../org/apache/spark/ml/param/shared/HasRawPredictionCol.html#getRawPredictionCol--), [rawPredictionCol](../../../../../org/apache/spark/ml/param/shared/HasRawPredictionCol.html#rawPredictionCol--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasRegParam](../../../../../org/apache/spark/ml/param/shared/HasRegParam.html "interface in org.apache.spark.ml.param.shared")  
   `[getRegParam](../../../../../org/apache/spark/ml/param/shared/HasRegParam.html#getRegParam--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasMaxIter](../../../../../org/apache/spark/ml/param/shared/HasMaxIter.html "interface in org.apache.spark.ml.param.shared")  
   `[getMaxIter](../../../../../org/apache/spark/ml/param/shared/HasMaxIter.html#getMaxIter--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasFitIntercept](../../../../../org/apache/spark/ml/param/shared/HasFitIntercept.html "interface in org.apache.spark.ml.param.shared")  
   `[getFitIntercept](../../../../../org/apache/spark/ml/param/shared/HasFitIntercept.html#getFitIntercept--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasTol](../../../../../org/apache/spark/ml/param/shared/HasTol.html "interface in org.apache.spark.ml.param.shared")  
   `[getTol](../../../../../org/apache/spark/ml/param/shared/HasTol.html#getTol--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasStandardization](../../../../../org/apache/spark/ml/param/shared/HasStandardization.html "interface in org.apache.spark.ml.param.shared")  
   `[getStandardization](../../../../../org/apache/spark/ml/param/shared/HasStandardization.html#getStandardization--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasWeightCol](../../../../../org/apache/spark/ml/param/shared/HasWeightCol.html "interface in org.apache.spark.ml.param.shared")  
   `[getWeightCol](../../../../../org/apache/spark/ml/param/shared/HasWeightCol.html#getWeightCol--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasAggregationDepth](../../../../../org/apache/spark/ml/param/shared/HasAggregationDepth.html "interface in org.apache.spark.ml.param.shared")  
   `[getAggregationDepth](../../../../../org/apache/spark/ml/param/shared/HasAggregationDepth.html#getAggregationDepth--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasThreshold](../../../../../org/apache/spark/ml/param/shared/HasThreshold.html "interface in org.apache.spark.ml.param.shared")  
   `[getThreshold](../../../../../org/apache/spark/ml/param/shared/HasThreshold.html#getThreshold--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasMaxBlockSizeInMB](../../../../../org/apache/spark/ml/param/shared/HasMaxBlockSizeInMB.html "interface in org.apache.spark.ml.param.shared")  
   `[getMaxBlockSizeInMB](../../../../../org/apache/spark/ml/param/shared/HasMaxBlockSizeInMB.html#getMaxBlockSizeInMB--)`  
   * ### Methods inherited from interface org.apache.spark.ml.util.[MLWritable](../../../../../org/apache/spark/ml/util/MLWritable.html "interface in org.apache.spark.ml.util")  
   `[save](../../../../../org/apache/spark/ml/util/MLWritable.html#save-java.lang.String-)`  
   * ### Methods inherited from interface org.apache.spark.ml.util.[HasTrainingSummary](../../../../../org/apache/spark/ml/util/HasTrainingSummary.html "interface in org.apache.spark.ml.util")  
   `[hasSummary](../../../../../org/apache/spark/ml/util/HasTrainingSummary.html#hasSummary--), [setSummary](../../../../../org/apache/spark/ml/util/HasTrainingSummary.html#setSummary-scala.Option-)`  
   * ### Methods inherited from interface org.apache.spark.internal.Logging  
   `$init$, initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, initLock, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log__$eq, org$apache$spark$internal$Logging$$log_, uninitialize`

Method Detail

 * #### read  
 public static [MLReader](../../../../../org/apache/spark/ml/util/MLReader.html "class in org.apache.spark.ml.util")<[LinearSVCModel](../../../../../org/apache/spark/ml/classification/LinearSVCModel.html "class in org.apache.spark.ml.classification")> read()  
 * #### load  
 public static [LinearSVCModel](../../../../../org/apache/spark/ml/classification/LinearSVCModel.html "class in org.apache.spark.ml.classification") load(String path)  
 * #### threshold  
 public final [DoubleParam](../../../../../org/apache/spark/ml/param/DoubleParam.html "class in org.apache.spark.ml.param") threshold()  
 Param for threshold in binary classification prediction. For LinearSVC, this threshold is applied to the rawPrediction, rather than a probability. This threshold can be any real number, where Inf will make all predictions 0.0 and -Inf will make all predictions 1.0\. Default: 0.0  
 Specified by:  
 `[threshold](../../../../../org/apache/spark/ml/classification/LinearSVCParams.html#threshold--)` in interface `[LinearSVCParams](../../../../../org/apache/spark/ml/classification/LinearSVCParams.html "interface in org.apache.spark.ml.classification")`  
 Specified by:  
 `[threshold](../../../../../org/apache/spark/ml/param/shared/HasThreshold.html#threshold--)` in interface `[HasThreshold](../../../../../org/apache/spark/ml/param/shared/HasThreshold.html "interface in org.apache.spark.ml.param.shared")`  
 Returns:  
 (undocumented)  
 * #### maxBlockSizeInMB  
 public final [DoubleParam](../../../../../org/apache/spark/ml/param/DoubleParam.html "class in org.apache.spark.ml.param") maxBlockSizeInMB()  
 Param for Maximum memory in MB for stacking input data into blocks. Data is stacked within partitions. If more than remaining data size in a partition then it is adjusted to the data size. Default 0.0 represents choosing optimal value, depends on specific algorithm. Must be &gt;= 0..  
 Specified by:  
 `[maxBlockSizeInMB](../../../../../org/apache/spark/ml/param/shared/HasMaxBlockSizeInMB.html#maxBlockSizeInMB--)` in interface `[HasMaxBlockSizeInMB](../../../../../org/apache/spark/ml/param/shared/HasMaxBlockSizeInMB.html "interface in org.apache.spark.ml.param.shared")`  
 Returns:  
 (undocumented)  
 * #### aggregationDepth  
 public final [IntParam](../../../../../org/apache/spark/ml/param/IntParam.html "class in org.apache.spark.ml.param") aggregationDepth()  
 Param for suggested depth for treeAggregate (&gt;= 2).  
 Specified by:  
 `[aggregationDepth](../../../../../org/apache/spark/ml/param/shared/HasAggregationDepth.html#aggregationDepth--)` in interface `[HasAggregationDepth](../../../../../org/apache/spark/ml/param/shared/HasAggregationDepth.html "interface in org.apache.spark.ml.param.shared")`  
 Returns:  
 (undocumented)  
 * #### weightCol  
 public final [Param](../../../../../org/apache/spark/ml/param/Param.html "class in org.apache.spark.ml.param")<String> weightCol()  
 Param for weight column name. If this is not set or empty, we treat all instance weights as 1.0.  
 Specified by:  
 `[weightCol](../../../../../org/apache/spark/ml/param/shared/HasWeightCol.html#weightCol--)` in interface `[HasWeightCol](../../../../../org/apache/spark/ml/param/shared/HasWeightCol.html "interface in org.apache.spark.ml.param.shared")`  
 Returns:  
 (undocumented)  
 * #### standardization  
 public final [BooleanParam](../../../../../org/apache/spark/ml/param/BooleanParam.html "class in org.apache.spark.ml.param") standardization()  
 Param for whether to standardize the training features before fitting the model.  
 Specified by:  
 `[standardization](../../../../../org/apache/spark/ml/param/shared/HasStandardization.html#standardization--)` in interface `[HasStandardization](../../../../../org/apache/spark/ml/param/shared/HasStandardization.html "interface in org.apache.spark.ml.param.shared")`  
 Returns:  
 (undocumented)  
 * #### tol  
 public final [DoubleParam](../../../../../org/apache/spark/ml/param/DoubleParam.html "class in org.apache.spark.ml.param") tol()  
 Description copied from interface: `[HasTol](../../../../../org/apache/spark/ml/param/shared/HasTol.html#tol--)`  
 Param for the convergence tolerance for iterative algorithms (&gt;= 0).  
 Specified by:  
 `[tol](../../../../../org/apache/spark/ml/param/shared/HasTol.html#tol--)` in interface `[HasTol](../../../../../org/apache/spark/ml/param/shared/HasTol.html "interface in org.apache.spark.ml.param.shared")`  
 Returns:  
 (undocumented)  
 * #### fitIntercept  
 public final [BooleanParam](../../../../../org/apache/spark/ml/param/BooleanParam.html "class in org.apache.spark.ml.param") fitIntercept()  
 Param for whether to fit an intercept term.  
 Specified by:  
 `[fitIntercept](../../../../../org/apache/spark/ml/param/shared/HasFitIntercept.html#fitIntercept--)` in interface `[HasFitIntercept](../../../../../org/apache/spark/ml/param/shared/HasFitIntercept.html "interface in org.apache.spark.ml.param.shared")`  
 Returns:  
 (undocumented)  
 * #### maxIter  
 public final [IntParam](../../../../../org/apache/spark/ml/param/IntParam.html "class in org.apache.spark.ml.param") maxIter()  
 Description copied from interface: `[HasMaxIter](../../../../../org/apache/spark/ml/param/shared/HasMaxIter.html#maxIter--)`  
 Param for maximum number of iterations (&gt;= 0).  
 Specified by:  
 `[maxIter](../../../../../org/apache/spark/ml/param/shared/HasMaxIter.html#maxIter--)` in interface `[HasMaxIter](../../../../../org/apache/spark/ml/param/shared/HasMaxIter.html "interface in org.apache.spark.ml.param.shared")`  
 Returns:  
 (undocumented)  
 * #### regParam  
 public final [DoubleParam](../../../../../org/apache/spark/ml/param/DoubleParam.html "class in org.apache.spark.ml.param") regParam()  
 Description copied from interface: `[HasRegParam](../../../../../org/apache/spark/ml/param/shared/HasRegParam.html#regParam--)`  
 Param for regularization parameter (&gt;= 0).  
 Specified by:  
 `[regParam](../../../../../org/apache/spark/ml/param/shared/HasRegParam.html#regParam--)` in interface `[HasRegParam](../../../../../org/apache/spark/ml/param/shared/HasRegParam.html "interface in org.apache.spark.ml.param.shared")`  
 Returns:  
 (undocumented)  
 * #### uid  
 public String uid()  
 An immutable unique ID for the object and its derivatives.  
 Specified by:  
 `[uid](../../../../../org/apache/spark/ml/util/Identifiable.html#uid--)` in interface `[Identifiable](../../../../../org/apache/spark/ml/util/Identifiable.html "interface in org.apache.spark.ml.util")`  
 Returns:  
 (undocumented)  
 * #### coefficients  
 public [Vector](../../../../../org/apache/spark/ml/linalg/Vector.html "interface in org.apache.spark.ml.linalg") coefficients()  
 * #### intercept  
 public double intercept()  
 * #### numClasses  
 public int numClasses()  
 Number of classes (values which the label can take).  
 Specified by:  
 `[numClasses](../../../../../org/apache/spark/ml/classification/ClassificationModel.html#numClasses--)` in class `[ClassificationModel](../../../../../org/apache/spark/ml/classification/ClassificationModel.html "class in org.apache.spark.ml.classification")<[Vector](../../../../../org/apache/spark/ml/linalg/Vector.html "interface in org.apache.spark.ml.linalg"),[LinearSVCModel](../../../../../org/apache/spark/ml/classification/LinearSVCModel.html "class in org.apache.spark.ml.classification")>`  
 * #### numFeatures  
 public int numFeatures()  
 Returns the number of features the model was trained on. If unknown, returns -1  
 Overrides:  
 `[numFeatures](../../../../../org/apache/spark/ml/PredictionModel.html#numFeatures--)` in class `[PredictionModel](../../../../../org/apache/spark/ml/PredictionModel.html "class in org.apache.spark.ml")<[Vector](../../../../../org/apache/spark/ml/linalg/Vector.html "interface in org.apache.spark.ml.linalg"),[LinearSVCModel](../../../../../org/apache/spark/ml/classification/LinearSVCModel.html "class in org.apache.spark.ml.classification")>`  
 * #### setThreshold  
 public [LinearSVCModel](../../../../../org/apache/spark/ml/classification/LinearSVCModel.html "class in org.apache.spark.ml.classification") setThreshold(double value)  
 * #### summary  
 public [LinearSVCTrainingSummary](../../../../../org/apache/spark/ml/classification/LinearSVCTrainingSummary.html "interface in org.apache.spark.ml.classification") summary()  
 Gets summary of model on training set. An exception is thrown if `hasSummary` is false.  
 Specified by:  
 `[summary](../../../../../org/apache/spark/ml/util/HasTrainingSummary.html#summary--)` in interface `[HasTrainingSummary](../../../../../org/apache/spark/ml/util/HasTrainingSummary.html "interface in org.apache.spark.ml.util")<[LinearSVCTrainingSummary](../../../../../org/apache/spark/ml/classification/LinearSVCTrainingSummary.html "interface in org.apache.spark.ml.classification")>`  
 Returns:  
 (undocumented)  
 * #### evaluate  
 public [LinearSVCSummary](../../../../../org/apache/spark/ml/classification/LinearSVCSummary.html "interface in org.apache.spark.ml.classification") evaluate([Dataset](../../../../../org/apache/spark/sql/Dataset.html "class in org.apache.spark.sql")<?> dataset)  
 Evaluates the model on a test dataset.  
 Parameters:  
 `dataset` \- Test dataset to evaluate model on.  
 Returns:  
 (undocumented)  
 * #### predict  
 public double predict([Vector](../../../../../org/apache/spark/ml/linalg/Vector.html "interface in org.apache.spark.ml.linalg") features)  
 Predict label for the given features. This method is used to implement `transform()` and output `predictionCol`.  
  This default implementation for classification predicts the index of the maximum value from `predictRaw()`.  
 Overrides:  
 `[predict](../../../../../org/apache/spark/ml/classification/ClassificationModel.html#predict-FeaturesType-)` in class `[ClassificationModel](../../../../../org/apache/spark/ml/classification/ClassificationModel.html "class in org.apache.spark.ml.classification")<[Vector](../../../../../org/apache/spark/ml/linalg/Vector.html "interface in org.apache.spark.ml.linalg"),[LinearSVCModel](../../../../../org/apache/spark/ml/classification/LinearSVCModel.html "class in org.apache.spark.ml.classification")>`  
 Parameters:  
 `features` \- (undocumented)  
 Returns:  
 (undocumented)  
 * #### predictRaw  
 public [Vector](../../../../../org/apache/spark/ml/linalg/Vector.html "interface in org.apache.spark.ml.linalg") predictRaw([Vector](../../../../../org/apache/spark/ml/linalg/Vector.html "interface in org.apache.spark.ml.linalg") features)  
 Raw prediction for each possible label. The meaning of a "raw" prediction may vary between algorithms, but it intuitively gives a measure of confidence in each possible label (where larger = more confident). This internal method is used to implement `transform()` and output `rawPredictionCol`.  
 Specified by:  
 `[predictRaw](../../../../../org/apache/spark/ml/classification/ClassificationModel.html#predictRaw-FeaturesType-)` in class `[ClassificationModel](../../../../../org/apache/spark/ml/classification/ClassificationModel.html "class in org.apache.spark.ml.classification")<[Vector](../../../../../org/apache/spark/ml/linalg/Vector.html "interface in org.apache.spark.ml.linalg"),[LinearSVCModel](../../../../../org/apache/spark/ml/classification/LinearSVCModel.html "class in org.apache.spark.ml.classification")>`  
 Parameters:  
 `features` \- (undocumented)  
 Returns:  
 vector where element i is the raw prediction for label i. This raw prediction may be any real number, where a larger value indicates greater confidence for that label.  
 * #### copy  
 public [LinearSVCModel](../../../../../org/apache/spark/ml/classification/LinearSVCModel.html "class in org.apache.spark.ml.classification") copy([ParamMap](../../../../../org/apache/spark/ml/param/ParamMap.html "class in org.apache.spark.ml.param") extra)  
 Description copied from interface: `[Params](../../../../../org/apache/spark/ml/param/Params.html#copy-org.apache.spark.ml.param.ParamMap-)`  
 Creates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly. See `defaultCopy()`.  
 Specified by:  
 `[copy](../../../../../org/apache/spark/ml/param/Params.html#copy-org.apache.spark.ml.param.ParamMap-)` in interface `[Params](../../../../../org/apache/spark/ml/param/Params.html "interface in org.apache.spark.ml.param")`  
 Specified by:  
 `[copy](../../../../../org/apache/spark/ml/Model.html#copy-org.apache.spark.ml.param.ParamMap-)` in class `[Model](../../../../../org/apache/spark/ml/Model.html "class in org.apache.spark.ml")<[LinearSVCModel](../../../../../org/apache/spark/ml/classification/LinearSVCModel.html "class in org.apache.spark.ml.classification")>`  
 Parameters:  
 `extra` \- (undocumented)  
 Returns:  
 (undocumented)  
 * #### write  
 public [MLWriter](../../../../../org/apache/spark/ml/util/MLWriter.html "class in org.apache.spark.ml.util") write()  
 Description copied from interface: `[MLWritable](../../../../../org/apache/spark/ml/util/MLWritable.html#write--)`  
 Returns an `MLWriter` instance for this ML instance.  
 Specified by:  
 `[write](../../../../../org/apache/spark/ml/util/MLWritable.html#write--)` in interface `[MLWritable](../../../../../org/apache/spark/ml/util/MLWritable.html "interface in org.apache.spark.ml.util")`  
 Returns:  
 (undocumented)  
 * #### toString  
 public String toString()  
 Specified by:  
 `[toString](../../../../../org/apache/spark/ml/util/Identifiable.html#toString--)` in interface `[Identifiable](../../../../../org/apache/spark/ml/util/Identifiable.html "interface in org.apache.spark.ml.util")`  
 Overrides:  
 `toString` in class `Object`

LinearSVCModel (Spark 3.5.5 JavaDoc) (original) (raw)

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