## Uses of Interface
org.apache.ignite.ml.inference.Model

- Packages that use Model
  Package | Description
  --- | ---
  org.apache.ignite.ml | Root ML package.
  org.apache.ignite.ml.clustering.gmm | Contains Gauss Mixture Model clustering algorithm (see `GmmModel`).
  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.bagging |
  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.composition.combinators.parallel | Contains parallel combiners (ensembles) of trainers and models.
  org.apache.ignite.ml.composition.combinators.sequential | Contains sequential combinators of trainers and models.
  org.apache.ignite.ml.composition.stacking | Contains classes used for training with stacking technique.
  org.apache.ignite.ml.h2o | Base package for H2O MOJO model parser.
  org.apache.ignite.ml.inference | Root package for model inference functionality.
  org.apache.ignite.ml.inference.builder | Root package for model inference builders.
  org.apache.ignite.ml.inference.parser | Root package for model inference parsers.
  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.knn.classification | Contains main APIs for kNN classification algorithms.
  org.apache.ignite.ml.knn.regression | Contains helper classes for kNN regression 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.nn | Contains neural networks and related classes.
  org.apache.ignite.ml.optimization | Contains implementations of optimization algorithms and related classes.
  org.apache.ignite.ml.pipeline | Contains Pipeline API.
  org.apache.ignite.ml.recommendation | Contains recommendation system framework.
  org.apache.ignite.ml.regressions.linear | Contains various linear regressions.
  org.apache.ignite.ml.regressions.logistic | Contains various logistic regressions.
  org.apache.ignite.ml.sparkmodelparser | Base package for Spark model parser.
  org.apache.ignite.ml.svm | Contains main APIs for SVM(support vector machines) algorithms.
  org.apache.ignite.ml.trainers | Contains model trainers.
  org.apache.ignite.ml.tree | Root package for decision trees.
  org.apache.ignite.ml.tree.randomforest.data | Package contains helper data structures for random forest implementation.
  org.apache.ignite.ml.xgboost | Base package for XGBoost model parser, correspondent DTOs and util classes.

- - ### Uses of Model in org.apache.ignite.ml

    Subinterfaces of Model in org.apache.ignite.ml
    Modifier and Type | Interface and Description
    --- | ---
    `interface` | `IgniteModel<T,V>` Basic interface for all models.

  - ### Uses of Model in org.apache.ignite.ml.clustering.gmm

    Classes in org.apache.ignite.ml.clustering.gmm that implement Model
    Modifier and Type | Class and Description
    --- | ---
    `class` | `GmmModel` Gaussian Mixture Model.

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

    Subinterfaces of Model in org.apache.ignite.ml.clustering.kmeans
    Modifier and Type | Interface and Description
    --- | ---
    `interface` | `ClusterizationModel<P,V>` Base interface for all clusterization models.

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

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

    Classes in org.apache.ignite.ml.composition that implement Model
    Modifier and Type | Class and Description
    --- | ---
    `class` | `ModelOnFeaturesSubspace` Model trained on a features subspace with mapping from original features space to subspace.
    `class` | `ModelsComposition` Model consisting of several models and prediction aggregation strategy.

  - ### Uses of Model in org.apache.ignite.ml.composition.bagging

    Classes in org.apache.ignite.ml.composition.bagging that implement Model
    Modifier and Type | Class and Description
    --- | ---
    `class` | `BaggedModel` This class represents model produced by `BaggedTrainer`.

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

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

  - ### Uses of Model in org.apache.ignite.ml.composition.combinators.parallel

    Classes in org.apache.ignite.ml.composition.combinators.parallel that implement Model
    Modifier and Type | Class and Description
    --- | ---
    `class` | `ModelsParallelComposition<I,O>` Parallel composition of models.

  - ### Uses of Model in org.apache.ignite.ml.composition.combinators.sequential

    Classes in org.apache.ignite.ml.composition.combinators.sequential that implement Model
    Modifier and Type | Class and Description
    --- | ---
    `class` | `ModelsSequentialComposition<I,O1,O2>` Sequential composition of models.

  - ### Uses of Model in org.apache.ignite.ml.composition.stacking

    Classes in org.apache.ignite.ml.composition.stacking that implement Model
    Modifier and Type | Class and Description
    --- | ---
    `class` | `StackedModel<IS,IA,O,AM extends IgniteModel<IA,O>>` This is a wrapper for model produced by `StackedDatasetTrainer`.

  - ### Uses of Model in org.apache.ignite.ml.h2o

    Classes in org.apache.ignite.ml.h2o that implement Model
    Modifier and Type | Class and Description
    --- | ---
    `class` | `H2OMojoModel` H2O MOJO Model imported and wrapped to be compatible with Apache Ignite infrastructure.

  - ### Uses of Model in org.apache.ignite.ml.inference

    Methods in org.apache.ignite.ml.inference that return Model
    Modifier and Type | Method and Description
    --- | ---
    `static Model<Vector,Future<Double>>` | IgniteModelStorageUtil.`getAsyncModel(Ignite ignite, String name, AsyncModelBuilder mdlBldr)` Retrieves Ignite model by name using asynchronous model builder.
    `static <I extends Serializable,O extends Serializable> Model<I,O>` | IgniteModelStorageUtil.`getModel(Ignite ignite, String name)` Retrieves Ignite model by name using `SingleModelBuilder`.
    `static <I extends Serializable,O extends Serializable> Model<I,O>` | IgniteModelStorageUtil.`getSyncModel(Ignite ignite, String name, SyncModelBuilder mdlBldr)` Retrieves Ignite model by name using synchronous model builder.

  - ### Uses of Model in org.apache.ignite.ml.inference.builder

    Methods in org.apache.ignite.ml.inference.builder with type parameters of type Model
    Modifier and Type | Method and Description
    --- | ---
    `<I extends Serializable,O extends Serializable,M extends Model<I,O>> M` | SingleModelBuilder.`build(ModelReader reader, ModelParser<I,O,M> parser)` Builds synchronous inference model using specified model reader and model parser.
    `<I extends Serializable,O extends Serializable,M extends Model<I,O>> M` | SyncModelBuilder.`build(ModelReader reader, ModelParser<I,O,M> parser)` Builds synchronous inference model using specified model reader and model parser.

    Methods in org.apache.ignite.ml.inference.builder that return Model
    Modifier and Type | Method and Description
    --- | ---
    `<I extends Serializable,O extends Serializable> Model<I,Future<O>>` | AsyncModelBuilder.`build(ModelReader reader, ModelParser<I,O,?> parser)` Builds asynchronous inference model using specified model reader and model parser.
    `<I extends Serializable,O extends Serializable> Model<I,Future<O>>` | ThreadedModelBuilder.`build(ModelReader reader, ModelParser<I,O,?> parser)` Builds asynchronous inference model using specified model reader and model parser.
    `<I extends Serializable,O extends Serializable> Model<I,Future<O>>` | IgniteDistributedModelBuilder.`build(ModelReader reader, ModelParser<I,O,?> parser)` Starts the specified in constructor number of service instances and request/response queues.

  - ### Uses of Model in org.apache.ignite.ml.inference.parser

    Classes in org.apache.ignite.ml.inference.parser with type parameters of type Model
    Modifier and Type | Interface and Description
    --- | ---
    `interface` | `ModelParser<I,O,M extends Model<I,O>>` Model parser that accepts a serialized model represented by byte array, parses it and returns `Model`.

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

    Classes in org.apache.ignite.ml.knn that implement Model
    Modifier and Type | Class and Description
    --- | ---
    `class` | `KNNModel<L>` KNN model build on top of distributed spatial indices.
    `class` | `NNClassificationModel` Common methods and fields for all kNN and aNN models to predict label based on neighbours' labels.

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

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

  - ### Uses of Model in org.apache.ignite.ml.knn.classification

    Classes in org.apache.ignite.ml.knn.classification that implement Model
    Modifier and Type | Class and Description
    --- | ---
    `class` | `KNNClassificationModel` KNN classification model.

  - ### Uses of Model in org.apache.ignite.ml.knn.regression

    Classes in org.apache.ignite.ml.knn.regression that implement Model
    Modifier and Type | Class and Description
    --- | ---
    `class` | `KNNRegressionModel` KNN regression model.

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

    Classes in org.apache.ignite.ml.multiclass that implement Model
    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 Model in org.apache.ignite.ml.naivebayes

    Subinterfaces of Model 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 Model in org.apache.ignite.ml.naivebayes.compound

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

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

    Classes in org.apache.ignite.ml.naivebayes.discrete that implement Model
    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 Model in org.apache.ignite.ml.naivebayes.gaussian

    Classes in org.apache.ignite.ml.naivebayes.gaussian that implement Model
    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 Model in org.apache.ignite.ml.nn

    Classes in org.apache.ignite.ml.nn that implement Model
    Modifier and Type | Class and Description
    --- | ---
    `class` | `MultilayerPerceptron` Class encapsulating logic of multilayer perceptron.

  - ### Uses of Model in org.apache.ignite.ml.optimization

    Subinterfaces of Model in org.apache.ignite.ml.optimization
    Modifier and Type | Interface and Description
    --- | ---
    `interface` | `SmoothParametrized<M extends Parametrized<M>>` Interface for models which are smooth functions of their parameters.

  - ### Uses of Model in org.apache.ignite.ml.pipeline

    Classes in org.apache.ignite.ml.pipeline that implement Model
    Modifier and Type | Class and Description
    --- | ---
    `class` | `PipelineMdl<K,V>` Wraps the model produced by `Pipeline`.

  - ### Uses of Model in org.apache.ignite.ml.recommendation

    Classes in org.apache.ignite.ml.recommendation that implement Model
    Modifier and Type | Class and Description
    --- | ---
    `class` | `RecommendationModel<O extends Serializable,S extends Serializable>` Recommendation model that predicts rating for `ObjectSubjectPair`.

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

    Classes in org.apache.ignite.ml.regressions.linear that implement Model
    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 Model in org.apache.ignite.ml.regressions.logistic

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

  - ### Uses of Model in org.apache.ignite.ml.sparkmodelparser

    Methods in org.apache.ignite.ml.sparkmodelparser that return Model
    Modifier and Type | Method and Description
    --- | ---
    `static Model` | SparkModelParser.`parse(String pathToMdl, SupportedSparkModels parsedSparkMdl)` Load model from parquet (presented as a directory).
    `static Model` | SparkModelParser.`parse(String pathToMdl, SupportedSparkModels parsedSparkMdl, LearningEnvironment learningEnvironment)` Load model from parquet (presented as a directory).

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

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

  - ### Uses of Model in org.apache.ignite.ml.trainers

    Classes in org.apache.ignite.ml.trainers that implement Model
    Modifier and Type | Class and Description
    --- | ---
    `class` | `AdaptableDatasetModel<I,O,IW,OW,M extends IgniteModel<IW,OW>>` Model which is composition of form `before `andThen` inner Mdl `andThen` after`.

  - ### Uses of Model in org.apache.ignite.ml.tree

    Subinterfaces of Model in org.apache.ignite.ml.tree
    Modifier and Type | Interface and Description
    --- | ---
    `interface` | `DecisionTreeNode` Base interface for decision tree nodes.

    Classes in org.apache.ignite.ml.tree that implement Model
    Modifier and Type | Class and Description
    --- | ---
    `class` | `DecisionTreeConditionalNode` Decision tree conditional (non-leaf) node.
    `class` | `DecisionTreeLeafNode` Decision tree leaf node which contains value.

  - ### Uses of Model in org.apache.ignite.ml.tree.randomforest.data

    Classes in org.apache.ignite.ml.tree.randomforest.data that implement Model
    Modifier and Type | Class and Description
    --- | ---
    `class` | `TreeNode` Decision tree node class.
    `class` | `TreeRoot` Tree root class.

  - ### Uses of Model in org.apache.ignite.ml.xgboost

    Classes in org.apache.ignite.ml.xgboost that implement Model
    Modifier and Type | Class and Description
    --- | ---
    `class` | `XGModelComposition` XGBoost model composition.

2020 Copyright © Apache Software Foundation
| Follow @ApacheIgnite
Ignite Database and Caching Platform | : ver. 2.9.0
Release Date | : October 15 2020