## Uses of Interface
org.apache.ignite.ml.Exportable

- Packages that use Exportable
  Package | Description
  --- | ---
  org.apache.ignite.ml.clustering.kmeans | Contains kMeans clustering algorithm.
  org.apache.ignite.ml.composition | Contains classes for ensemble of models implementation.
  org.apache.ignite.ml.composition.boosting | Contains Gradient Boosting regression and classification abstract classes allowing regressor type selecting in child classes.
  org.apache.ignite.ml.knn | Contains main APIs for kNN algorithms.
  org.apache.ignite.ml.knn.ann | Contains main APIs for ANN classification algorithms.
  org.apache.ignite.ml.multiclass | Contains various multi-classifier models and trainers.
  org.apache.ignite.ml.naivebayes | Contains various naive Bayes classifiers.
  org.apache.ignite.ml.naivebayes.compound | Contains Compound naive Bayes classifier.
  org.apache.ignite.ml.naivebayes.discrete | Contains Bernoulli naive Bayes classifier.
  org.apache.ignite.ml.naivebayes.gaussian | Contains Gaussian naive Bayes classifier.
  org.apache.ignite.ml.regressions.linear | Contains various linear regressions.
  org.apache.ignite.ml.regressions.logistic | Contains various logistic regressions.
  org.apache.ignite.ml.svm | Contains main APIs for SVM(support vector machines) algorithms.

- - ### Uses of Exportable in org.apache.ignite.ml.clustering.kmeans

    Classes in org.apache.ignite.ml.clustering.kmeans that implement Exportable
    Modifier and Type | Class and Description
    --- | ---
    `class` | `KMeansModel` This class encapsulates result of clusterization by KMeans algorithm.

  - ### Uses of Exportable in org.apache.ignite.ml.composition

    Classes in org.apache.ignite.ml.composition that implement Exportable
    Modifier and Type | Class and Description
    --- | ---
    `class` | `ModelsComposition` Model consisting of several models and prediction aggregation strategy.

  - ### Uses of Exportable in org.apache.ignite.ml.composition.boosting

    Classes in org.apache.ignite.ml.composition.boosting that implement Exportable
    Modifier and Type | Class and Description
    --- | ---
    `static class` | `GDBTrainer.GDBModel` GDB model.

  - ### Uses of Exportable in org.apache.ignite.ml.knn

    Classes in org.apache.ignite.ml.knn that implement Exportable
    Modifier and Type | Class and Description
    --- | ---
    `class` | `NNClassificationModel` Common methods and fields for all kNN and aNN models to predict label based on neighbours' labels.

  - ### Uses of Exportable in org.apache.ignite.ml.knn.ann

    Classes in org.apache.ignite.ml.knn.ann that implement Exportable
    Modifier and Type | Class and Description
    --- | ---
    `class` | `ANNClassificationModel` ANN model to predict labels in multi-class classification task.

  - ### Uses of Exportable in org.apache.ignite.ml.multiclass

    Classes in org.apache.ignite.ml.multiclass that implement Exportable
    Modifier and Type | Class and Description
    --- | ---
    `class` | `MultiClassModel<M extends IgniteModel<Vector,Double>>` Base class for multi-classification model for set of classifiers.

  - ### Uses of Exportable in org.apache.ignite.ml.naivebayes

    Subinterfaces of Exportable in org.apache.ignite.ml.naivebayes
    Modifier and Type | Interface and Description
    --- | ---
    `interface` | `BayesModel<MODEL extends BayesModel,FEATURES,OUTPUT>` Interface for Bayes Models.

  - ### Uses of Exportable in org.apache.ignite.ml.naivebayes.compound

    Classes in org.apache.ignite.ml.naivebayes.compound that implement Exportable
    Modifier and Type | Class and Description
    --- | ---
    `class` | `CompoundNaiveBayesModel` A compound Naive Bayes model which uses a composition of`GaussianNaiveBayesModel` and `DiscreteNaiveBayesModel`.

  - ### Uses of Exportable in org.apache.ignite.ml.naivebayes.discrete

    Classes in org.apache.ignite.ml.naivebayes.discrete that implement Exportable
    Modifier and Type | Class and Description
    --- | ---
    `class` | `DiscreteNaiveBayesModel` Discrete naive Bayes model which predicts result value `y` belongs to a class `C_k, k in [0..K]` as {@code p(C_k,y) =x_1*p_k1^x *...

  - ### Uses of Exportable in org.apache.ignite.ml.naivebayes.gaussian

    Classes in org.apache.ignite.ml.naivebayes.gaussian that implement Exportable
    Modifier and Type | Class and Description
    --- | ---
    `class` | `GaussianNaiveBayesModel` Simple naive Bayes model which predicts result value `y` belongs to a class `C_k, k in [0..K]` as {@code p(C_k,y) = p(C_k)*p(y_1,C_k) *...

  - ### Uses of Exportable in org.apache.ignite.ml.regressions.linear

    Classes in org.apache.ignite.ml.regressions.linear that implement Exportable
    Modifier and Type | Class and Description
    --- | ---
    `class` | `LinearRegressionModel` Simple linear regression model which predicts result value Y as a linear combination of input variables: Y = weights * X + intercept.

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

    Classes in org.apache.ignite.ml.regressions.logistic that implement Exportable
    Modifier and Type | Class and Description
    --- | ---
    `class` | `LogisticRegressionModel` Logistic regression (logit model) is a generalized linear model used for binomial regression.

  - ### Uses of Exportable in org.apache.ignite.ml.svm

    Classes in org.apache.ignite.ml.svm that implement Exportable
    Modifier and Type | Class and Description
    --- | ---
    `class` | `SVMLinearClassificationModel` Base class for SVM linear classification model.

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Release Date | : December 9 2020