public class SVMModel extends GeneralizedLinearModel implements ClassificationModel, scala.Serializable, Saveable, PMMLExportable
param: weights Weights computed for every feature. param: intercept Intercept computed for this model.
Constructor and Description |
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SVMModel(Vector weights,
double intercept) |
Modifier and Type | Method and Description |
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SVMModel |
clearThreshold()
Clears the threshold so that
predict will output raw prediction scores. |
scala.Option<Object> |
getThreshold()
Returns the threshold (if any) used for converting raw prediction scores into 0/1 predictions.
|
double |
intercept() |
static SVMModel |
load(SparkContext sc,
String path) |
void |
save(SparkContext sc,
String path)
Save this model to the given path.
|
SVMModel |
setThreshold(double threshold)
Sets the threshold that separates positive predictions from negative predictions.
|
String |
toString()
Print a summary of the model.
|
Vector |
weights() |
predict, predict
predict, predict, predict
public SVMModel(Vector weights, double intercept)
public static SVMModel load(SparkContext sc, String path)
public Vector weights()
weights
in class GeneralizedLinearModel
public double intercept()
intercept
in class GeneralizedLinearModel
public SVMModel setThreshold(double threshold)
threshold
- (undocumented)public scala.Option<Object> getThreshold()
public SVMModel clearThreshold()
predict
will output raw prediction scores.public void save(SparkContext sc, String path)
Saveable
This saves: - human-readable (JSON) model metadata to path/metadata/ - Parquet formatted data to path/data/
The model may be loaded using Loader.load
.
public String toString()
GeneralizedLinearModel
toString
in class GeneralizedLinearModel