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.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.
|
Modifier and Type | Class and Description |
---|---|
class |
KMeansModel
This class encapsulates result of clusterization by KMeans algorithm.
|
Modifier and Type | Class and Description |
---|---|
class |
ModelsComposition
Model consisting of several models and prediction aggregation strategy.
|
Modifier and Type | Class and Description |
---|---|
static class |
GDBTrainer.GDBModel
GDB model.
|
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.
|
Modifier and Type | Class and Description |
---|---|
class |
ANNClassificationModel
ANN model to predict labels in multi-class classification task.
|
Modifier and Type | Class and Description |
---|---|
class |
MultiClassModel<M extends IgniteModel<Vector,Double>>
Base class for multi-classification model for set of classifiers.
|
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 *... |
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) *... |
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.
|
Modifier and Type | Class and Description |
---|---|
class |
LogisticRegressionModel
Logistic regression (logit model) is a generalized linear model used for binomial regression.
|
Modifier and Type | Class and Description |
---|---|
class |
SVMLinearClassificationModel
Base class for SVM linear classification model.
|
GridGain In-Memory Computing Platform : ver. 8.9.14 Release Date : November 5 2024