Class SVMModel
Object
org.apache.spark.mllib.regression.GeneralizedLinearModel
org.apache.spark.mllib.classification.SVMModel
- All Implemented Interfaces:
- Serializable,- ClassificationModel,- PMMLExportable,- Saveable
public class SVMModel
extends GeneralizedLinearModel
implements ClassificationModel, Serializable, Saveable, PMMLExportable
Model for Support Vector Machines (SVMs).
 
param: weights Weights computed for every feature. param: intercept Intercept computed for this model.
- See Also:
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Constructor SummaryConstructors
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Method SummaryModifier and TypeMethodDescriptionClears the threshold so thatpredictwill output raw prediction scores.scala.Option<Object>Returns the threshold (if any) used for converting raw prediction scores into 0/1 predictions.doublestatic SVMModelload(SparkContext sc, String path) voidsave(SparkContext sc, String path) Save this model to the given path.setThreshold(double threshold) Sets the threshold that separates positive predictions from negative predictions.toString()Print a summary of the model.weights()Methods inherited from class org.apache.spark.mllib.regression.GeneralizedLinearModelpredict, predictMethods inherited from class java.lang.Objectequals, getClass, hashCode, notify, notifyAll, wait, wait, waitMethods inherited from interface org.apache.spark.mllib.classification.ClassificationModelpredict, predict, predict
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Constructor Details- 
SVMModel
 
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Method Details- 
load
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weights- Overrides:
- weightsin class- GeneralizedLinearModel
 
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interceptpublic double intercept()- Overrides:
- interceptin class- GeneralizedLinearModel
 
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setThresholdSets the threshold that separates positive predictions from negative predictions. An example with prediction score greater than or equal to this threshold is identified as a positive, and negative otherwise. The default value is 0.0.- Parameters:
- threshold- (undocumented)
- Returns:
- (undocumented)
 
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getThresholdReturns the threshold (if any) used for converting raw prediction scores into 0/1 predictions.- Returns:
- (undocumented)
 
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clearThresholdClears the threshold so thatpredictwill output raw prediction scores.- Returns:
- (undocumented)
 
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saveDescription copied from interface:SaveableSave this model to the given path.This saves: - human-readable (JSON) model metadata to path/metadata/ - Parquet formatted data to path/data/ The model may be loaded using Loader.load.
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toStringDescription copied from class:GeneralizedLinearModelPrint a summary of the model.- Overrides:
- toStringin class- GeneralizedLinearModel
- Returns:
- (undocumented)
 
 
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