Uses of Class
org.apache.ignite.ml.regressions.logistic.binomial.LogisticRegressionModel

Packages that use LogisticRegressionModel

Package	Description
org.apache.ignite.ml.regressions.logistic.binomial	Contains binomial logistic regression.
org.apache.ignite.ml.regressions.logistic.multiclass	Contains multi-class logistic regression.

Uses of LogisticRegressionModel in org.apache.ignite.ml.regressions.logistic.binomial

Methods in org.apache.ignite.ml.regressions.logistic.binomial that return LogisticRegressionModel

Modifier and Type	Method and Description
<K,V> LogisticRegressionModel	LogisticRegressionSGDTrainer.fit(DatasetBuilder<K,V> datasetBuilder, IgniteBiFunction<K,V,Vector> featureExtractor, IgniteBiFunction<K,V,Double> lbExtractor) Trains model based on the specified data.
protected <K,V> LogisticRegressionModel	LogisticRegressionSGDTrainer.updateModel(LogisticRegressionModel mdl, DatasetBuilder<K,V> datasetBuilder, IgniteBiFunction<K,V,Vector> featureExtractor, IgniteBiFunction<K,V,Double> lbExtractor) Gets state of model in arguments, update in according to new data and return new model.
LogisticRegressionModel	LogisticRegressionModel.withIntercept(double intercept) Set up the intercept.
LogisticRegressionModel	LogisticRegressionModel.withRawLabels(boolean isKeepingRawLabels) Set up the output label format.
LogisticRegressionModel	LogisticRegressionModel.withThreshold(double threshold) Set up the threshold.
LogisticRegressionModel	LogisticRegressionModel.withWeights(Vector weights) Set up the weights.

Methods in org.apache.ignite.ml.regressions.logistic.binomial with parameters of type LogisticRegressionModel

Modifier and Type	Method and Description
protected boolean	LogisticRegressionSGDTrainer.checkState(LogisticRegressionModel mdl)
protected <K,V> LogisticRegressionModel	LogisticRegressionSGDTrainer.updateModel(LogisticRegressionModel mdl, DatasetBuilder<K,V> datasetBuilder, IgniteBiFunction<K,V,Vector> featureExtractor, IgniteBiFunction<K,V,Double> lbExtractor) Gets state of model in arguments, update in according to new data and return new model.

Method parameters in org.apache.ignite.ml.regressions.logistic.binomial with type arguments of type LogisticRegressionModel

Modifier and Type	Method and Description
<P> void	LogisticRegressionModel.saveModel(Exporter<LogisticRegressionModel,P> exporter, P path) Save model by the given path.

Uses of LogisticRegressionModel in org.apache.ignite.ml.regressions.logistic.multiclass

Methods in org.apache.ignite.ml.regressions.logistic.multiclass that return types with arguments of type LogisticRegressionModel

Modifier and Type	Method and Description
Optional<LogisticRegressionModel>	LogRegressionMultiClassModel.getModel(Double clsLb)

Methods in org.apache.ignite.ml.regressions.logistic.multiclass with parameters of type LogisticRegressionModel

Modifier and Type	Method and Description
void	LogRegressionMultiClassModel.add(double clsLb, LogisticRegressionModel mdl) Adds a specific Log Regression binary classifier to the bunch of same classifiers.