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	Contains bootstrap aggregation (bagging) trainer allowing to combine some other trainers and return a bagged version of them.
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 combinators 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.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.mleap	Base package for Mleap model parser.
org.apache.ignite.ml.multiclass	Contains various multi-classifier models and trainers.
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.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>>	IgniteDistributedModelBuilder.build(ModelReader reader, ModelParser<I,O,?> parser) Starts the specified in constructor number of service instances and request/response queues.
<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.

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.

Methods in org.apache.ignite.ml.inference.parser that return Model

Modifier and Type	Method and Description
Model<I,O>	TensorFlowBaseModelParser.parse(byte[] mdl) Accepts 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 distribtued 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.mleap

Classes in org.apache.ignite.ml.mleap that implement Model

Modifier and Type	Class and Description
class	MLeapModel MLeap model imported and wrapped to be compatible with Apache Ignite infrastructure.

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.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).

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.