public class SVMModel extends GeneralizedLinearModel implements ClassificationModel, scala.Serializable, Saveable
Constructor and Description |
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SVMModel(Vector weights,
double intercept) |
Modifier and Type | Method and Description |
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SVMModel |
clearThreshold()
:: Experimental ::
Clears the threshold so that
predict will output raw prediction scores. |
scala.Option<Object> |
getThreshold()
:: Experimental ::
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)
:: Experimental ::
Sets the threshold that separates positive predictions from negative predictions.
|
Vector |
weights() |
predict, predict, toString
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)
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
.