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 Summary
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Method Summary
Modifier and TypeMethodDescriptionClears the threshold so thatpredict
will output raw prediction scores.scala.Option<Object>
Returns the threshold (if any) used for converting raw prediction scores into 0/1 predictions.double
static SVMModel
load
(SparkContext sc, String path) void
save
(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.GeneralizedLinearModel
predict, predict
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait
Methods inherited from interface org.apache.spark.mllib.classification.ClassificationModel
predict, predict, predict
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Constructor Details
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SVMModel
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Method Details
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load
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weights
- Overrides:
weights
in classGeneralizedLinearModel
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intercept
public double intercept()- Overrides:
intercept
in classGeneralizedLinearModel
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setThreshold
Sets 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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getThreshold
Returns the threshold (if any) used for converting raw prediction scores into 0/1 predictions.- Returns:
- (undocumented)
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clearThreshold
Clears the threshold so thatpredict
will output raw prediction scores.- Returns:
- (undocumented)
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save
Description copied from interface:Saveable
Save 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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toString
Description copied from class:GeneralizedLinearModel
Print a summary of the model.- Overrides:
toString
in classGeneralizedLinearModel
- Returns:
- (undocumented)
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