Package org.apache.spark.ml.classification

Class FMClassificationModel

Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Transformer

org.apache.spark.ml.Model<M>

org.apache.spark.ml.PredictionModel<FeaturesType,M>

org.apache.spark.ml.classification.ClassificationModel<FeaturesType,M>

org.apache.spark.ml.classification.ProbabilisticClassificationModel<Vector,FMClassificationModel>

org.apache.spark.ml.classification.FMClassificationModel

All Implemented Interfaces:

Serializable, org.apache.spark.internal.Logging, ClassifierParams, FMClassifierParams, ProbabilisticClassifierParams, Params, HasFeaturesCol, HasFitIntercept, HasLabelCol, HasMaxIter, HasPredictionCol, HasProbabilityCol, HasRawPredictionCol, HasRegParam, HasSeed, HasSolver, HasStepSize, HasThresholds, HasTol, HasWeightCol, PredictorParams, FactorizationMachinesParams, HasTrainingSummary<FMClassificationTrainingSummary>, Identifiable, MLWritable

public class FMClassificationModel
extends ProbabilisticClassificationModel<Vector,FMClassificationModel>
implements FMClassifierParams, MLWritable, HasTrainingSummary<FMClassificationTrainingSummary>

Model produced by FMClassifier

See Also:

• Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging

org.apache.spark.internal.Logging.LogStringContext, org.apache.spark.internal.Logging.SparkShellLoggingFilter

Method Summary

Modifier and Type	Method	Description
FMClassificationModel	copy(ParamMap extra)	Creates a copy of this instance with the same UID and some extra params.
FMClassificationSummary	evaluate(Dataset<?> dataset)	Evaluates the model on a test dataset.
Matrix	factors()
final IntParam	factorSize()	Param for dimensionality of the factors (&gt;= 0)
final BooleanParam	fitIntercept()	Param for whether to fit an intercept term.
final BooleanParam	fitLinear()	Param for whether to fit linear term (aka 1-way term)
final DoubleParam	initStd()	Param for standard deviation of initial coefficients
double	intercept()
Vector	linear()
static FMClassificationModel	load(String path)
final IntParam	maxIter()	Param for maximum number of iterations (&gt;= 0).
final DoubleParam	miniBatchFraction()	Param for mini-batch fraction, must be in range (0, 1]
int	numClasses()	Number of classes (values which the label can take).
int	numFeatures()	Returns the number of features the model was trained on.
Vector	predictRaw(Vector features)	Raw prediction for each possible label.
static MLReader<FMClassificationModel>	read()
final DoubleParam	regParam()	Param for regularization parameter (&gt;= 0).
final LongParam	seed()	Param for random seed.
final Param<String>	solver()	The solver algorithm for optimization.
DoubleParam	stepSize()	Param for Step size to be used for each iteration of optimization (&gt; 0).
FMClassificationTrainingSummary	summary()	Gets summary of model on training set.
final DoubleParam	tol()	Param for the convergence tolerance for iterative algorithms (&gt;= 0).
String	toString()
String	uid()	An immutable unique ID for the object and its derivatives.
final Param<String>	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.ProbabilisticClassificationModel

normalizeToProbabilitiesInPlace, predictProbability, probabilityCol, setProbabilityCol, setThresholds, thresholds, transform, transformSchema

Methods inherited from class org.apache.spark.ml.classification.ClassificationModel

predict, rawPredictionCol, setRawPredictionCol, transformImpl

Methods inherited from class org.apache.spark.ml.PredictionModel

featuresCol, labelCol, predictionCol, setFeaturesCol, setPredictionCol

Methods inherited from class org.apache.spark.ml.Model

hasParent, parent, setParent

Methods inherited from class org.apache.spark.ml.Transformer

transform, transform, transform

Methods inherited from class org.apache.spark.ml.PipelineStage

params

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface org.apache.spark.ml.regression.FactorizationMachinesParams

getFactorSize, getFitLinear, getInitStd, getMiniBatchFraction

Methods inherited from interface org.apache.spark.ml.param.shared.HasFeaturesCol

featuresCol, getFeaturesCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasFitIntercept

getFitIntercept

Methods inherited from interface org.apache.spark.ml.param.shared.HasLabelCol

getLabelCol, labelCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasMaxIter

getMaxIter

Methods inherited from interface org.apache.spark.ml.param.shared.HasPredictionCol

getPredictionCol, predictionCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasProbabilityCol

getProbabilityCol, probabilityCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasRawPredictionCol

getRawPredictionCol, rawPredictionCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasRegParam

getRegParam

Methods inherited from interface org.apache.spark.ml.param.shared.HasSeed

getSeed

Methods inherited from interface org.apache.spark.ml.param.shared.HasSolver

getSolver

Methods inherited from interface org.apache.spark.ml.param.shared.HasStepSize

getStepSize

Methods inherited from interface org.apache.spark.ml.param.shared.HasThresholds

getThresholds, thresholds

Methods inherited from interface org.apache.spark.ml.param.shared.HasTol

getTol

Methods inherited from interface org.apache.spark.ml.util.HasTrainingSummary

hasSummary, setSummary

Methods inherited from interface org.apache.spark.ml.param.shared.HasWeightCol

getWeightCol

Methods inherited from interface org.apache.spark.internal.Logging

initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logDebug, logDebug, logDebug, logDebug, logError, logError, logError, logError, logInfo, logInfo, logInfo, logInfo, logName, LogStringContext, logTrace, logTrace, logTrace, logTrace, logWarning, logWarning, logWarning, logWarning, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq, withLogContext

Methods inherited from interface org.apache.spark.ml.util.MLWritable

save

Methods inherited from interface org.apache.spark.ml.param.Params

clear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn

Methods inherited from interface org.apache.spark.ml.classification.ProbabilisticClassifierParams

validateAndTransformSchema

Method Details

read

public static MLReader<FMClassificationModel> read()

load

public static FMClassificationModel load(String path)

factorSize

public final IntParam factorSize()

Description copied from interface: FactorizationMachinesParams

Param for dimensionality of the factors (&gt;= 0)

Specified by:

factorSize in interface