org.apache.ignite.ml.regressions.logistic

Class LogisticRegressionModel

java.lang.Object

org.apache.ignite.ml.regressions.logistic.LogisticRegressionModel

All Implemented Interfaces:

Serializable, AutoCloseable, Exportable<LogisticRegressionModel>, IgniteModel<Vector,Double>, Model<Vector,Double>

public final class LogisticRegressionModel
extends Object
implements IgniteModel<Vector,Double>, Exportable<LogisticRegressionModel>, Serializable

Logistic regression (logit model) is a generalized linear model used for binomial regression.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
LogisticRegressionModel(Vector weights, double intercept)

Method Summary

Modifier and Type	Method and Description
boolean	equals(Object o)
int	hashCode()
double	intercept() Gets the intercept.
boolean	isKeepingRawLabels() Gets the output label format mode.
Double	predict(Vector input) Make a prediction for the specified input arguments.
<P> void	saveModel(Exporter<LogisticRegressionModel,P> exporter, P path) Save model by the given path.
double	threshold() Gets the threshold.
String	toString()
String	toString(boolean pretty)
Vector	weights() Gets the weights.
LogisticRegressionModel	withIntercept(double intercept) Set up the intercept.
LogisticRegressionModel	withRawLabels(boolean isKeepingRawLabels) Set up the output label format.
LogisticRegressionModel	withThreshold(double threshold) Set up the threshold.
LogisticRegressionModel	withWeights(Vector weights) Set up the weights.

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface org.apache.ignite.ml.IgniteModel

andBefore, andThen, andThen, close, combine

Constructor Detail

LogisticRegressionModel

public LogisticRegressionModel(Vector weights,
                               double intercept)

Method Detail

withRawLabels

public LogisticRegressionModel withRawLabels(boolean isKeepingRawLabels)

Set up the output label format.

Parameters:

isKeepingRawLabels - The parameter value.

Returns:

Model with new isKeepingRawLabels parameter value.

withThreshold

public LogisticRegressionModel withThreshold(double threshold)

Set up the threshold.

Parameters:

threshold - The parameter value.

Returns:

Model with new threshold parameter value.

withWeights

public LogisticRegressionModel withWeights(Vector weights)

Set up the weights.

Parameters:

weights - The parameter value.

Returns:

Model with new weights parameter value.

withIntercept

public LogisticRegressionModel withIntercept(double intercept)

Set up the intercept.

Parameters:

intercept - The parameter value.

Returns:

Model with new intercept parameter value.

isKeepingRawLabels

public boolean isKeepingRawLabels()

Gets the output label format mode.

Returns:

The parameter value.

threshold

public double threshold()

Gets the threshold.

Returns:

The parameter value.

weights

public Vector weights()

Gets the weights.

Returns:

The parameter value.

intercept

public double intercept()

Gets the intercept.

Returns:

The parameter value.

predict

public Double predict(Vector input)

Make a prediction for the specified input arguments.

Specified by:

predict in interface Model<Vector,Double>

Parameters:

input - Input arguments.

Returns:

Prediction result.

saveModel

public <P> void saveModel(Exporter<LogisticRegressionModel,P> exporter,
                          P path)

Save model by the given path.

Specified by:

saveModel in interface Exportable<LogisticRegressionModel>

Parameters:

exporter - Exporter.

path - Path to saved model.

equals

public boolean equals(Object o)

Overrides:

equals in class Object

hashCode

public int hashCode()

Overrides:

hashCode in class Object

toString

public String toString()

Overrides:

toString in class Object

toString

public String toString(boolean pretty)

Specified by:

toString in interface IgniteModel<Vector,Double>

Parameters:

pretty - Use pretty mode.