Package org.apache.spark.ml.regression
Interface FactorizationMachinesParams
- All Superinterfaces:
- HasFeaturesCol,- HasFitIntercept,- HasLabelCol,- HasMaxIter,- HasPredictionCol,- HasRegParam,- HasSeed,- HasSolver,- HasStepSize,- HasTol,- HasWeightCol,- Identifiable,- Params,- PredictorParams,- Serializable
- All Known Subinterfaces:
- FactorizationMachines,- FMClassifierParams,- FMRegressorParams
- All Known Implementing Classes:
- FMClassificationModel,- FMClassifier,- FMRegressionModel,- FMRegressor
public interface FactorizationMachinesParams
extends PredictorParams, HasMaxIter, HasStepSize, HasTol, HasSolver, HasSeed, HasFitIntercept, HasRegParam, HasWeightCol
Params for Factorization Machines
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Method SummaryModifier and TypeMethodDescriptionParam for dimensionality of the factors (>= 0)Param for whether to fit linear term (aka 1-way term)intbooleandoubledoubleinitStd()Param for standard deviation of initial coefficientsParam for mini-batch fraction, must be in range (0, 1]solver()The solver algorithm for optimization.Methods inherited from interface org.apache.spark.ml.param.shared.HasFeaturesColfeaturesCol, getFeaturesColMethods inherited from interface org.apache.spark.ml.param.shared.HasFitInterceptfitIntercept, getFitInterceptMethods inherited from interface org.apache.spark.ml.param.shared.HasLabelColgetLabelCol, labelColMethods inherited from interface org.apache.spark.ml.param.shared.HasMaxItergetMaxIter, maxIterMethods inherited from interface org.apache.spark.ml.param.shared.HasPredictionColgetPredictionCol, predictionColMethods inherited from interface org.apache.spark.ml.param.shared.HasRegParamgetRegParam, regParamMethods inherited from interface org.apache.spark.ml.param.shared.HasStepSizegetStepSize, stepSizeMethods inherited from interface org.apache.spark.ml.param.shared.HasWeightColgetWeightCol, weightColMethods inherited from interface org.apache.spark.ml.util.IdentifiabletoString, uidMethods inherited from interface org.apache.spark.ml.param.Paramsclear, copy, copyValues, defaultCopy, defaultParamMap, estimateMatadataSize, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwnMethods inherited from interface org.apache.spark.ml.PredictorParamsvalidateAndTransformSchema
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Method Details- 
factorSizeIntParam factorSize()Param for dimensionality of the factors (>= 0)- Returns:
- (undocumented)
 
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fitLinearBooleanParam fitLinear()Param for whether to fit linear term (aka 1-way term)- Returns:
- (undocumented)
 
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getFactorSizeint getFactorSize()
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getFitLinearboolean getFitLinear()
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getInitStddouble getInitStd()
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getMiniBatchFractiondouble getMiniBatchFraction()
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initStdDoubleParam initStd()Param for standard deviation of initial coefficients- Returns:
- (undocumented)
 
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miniBatchFractionDoubleParam miniBatchFraction()Param for mini-batch fraction, must be in range (0, 1]- Returns:
- (undocumented)
 
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solverThe solver algorithm for optimization. Supported options: "gd", "adamW". Default: "adamW"
 
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