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

- Packages that use LogisticRegressionModel
  Package | Description
  --- | ---
  org.apache.ignite.ml.regressions.logistic | Contains various logistic regressions.

- - ### Uses of LogisticRegressionModel in org.apache.ignite.ml.regressions.logistic

    Methods in org.apache.ignite.ml.regressions.logistic that return LogisticRegressionModel
    Modifier and Type | Method and Description
    --- | ---
    `LogisticRegressionModel` | LogisticRegressionModel.LogisticRegressionJSONExportModel.`convert()` Convert JSON string to IgniteModel object.
    `<K,V> LogisticRegressionModel` | LogisticRegressionSGDTrainer.`fitWithInitializedDeployingContext(DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> extractor)` Trains model based on the specified data.
    `static LogisticRegressionModel` | LogisticRegressionModel.`fromJSON(Path path)` Loads KMeansModel from JSON file.
    `protected <K,V> LogisticRegressionModel` | LogisticRegressionSGDTrainer.`updateModel(LogisticRegressionModel mdl, DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> extractor)` 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 with parameters of type LogisticRegressionModel
    Modifier and Type | Method and Description
    --- | ---
    `boolean` | LogisticRegressionSGDTrainer.`isUpdateable(LogisticRegressionModel mdl)`
    `protected <K,V> LogisticRegressionModel` | LogisticRegressionSGDTrainer.`updateModel(LogisticRegressionModel mdl, DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> extractor)` 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 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.

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Release Date | : April 25 2023