Package | Description |
---|---|
org.tribuo.classification |
Provides classes and infrastructure for multiclass classification problems.
|
org.tribuo.classification.dtree |
Provides implementations of decision trees for classification problems.
|
org.tribuo.classification.experiments |
Provides a set of main methods for interacting with classification tasks.
|
org.tribuo.classification.liblinear |
Provides an interface to LibLinear-java for classification problems.
|
org.tribuo.classification.libsvm |
Provides an interface to LibSVM for classification problems.
|
org.tribuo.classification.mnb |
Provides an implementation of multinomial naive bayes (i.e., naive bayes for non-negative count data).
|
org.tribuo.classification.sgd |
Provides infrastructure for Stochastic Gradient Descent for classification problems.
|
org.tribuo.classification.sgd.kernel |
Provides a SGD implementation of a Kernel SVM using the Pegasos algorithm.
|
org.tribuo.classification.xgboost |
Provides an interface to XGBoost for classification problems.
|
org.tribuo.clustering.kmeans |
Provides a multithreaded implementation of K-Means, with a
configurable distance function.
|
org.tribuo.data |
Provides classes for loading in data from disk, processing it into examples, and splitting datasets for
things like cross-validation and train-test splits.
|
org.tribuo.regression.liblinear |
Provides an interface to liblinear for regression problems.
|
org.tribuo.regression.libsvm |
Provides an interface to LibSVM for regression problems.
|
org.tribuo.regression.rtree |
Provides an implementation of decision trees for regression problems.
|
org.tribuo.regression.sgd |
Provides infrastructure for Stochastic Gradient Descent based regression models.
|
org.tribuo.regression.slm |
Provides implementations of sparse linear regression using various forms of regularisation penalty.
|
org.tribuo.regression.xgboost |
Provides an interface to XGBoost for regression problems.
|
Modifier and Type | Method and Description |
---|---|
static Model<Label> |
TrainTestHelper.run(com.oracle.labs.mlrg.olcut.config.ConfigurationManager cm,
DataOptions dataOptions,
Trainer<Label> trainer)
This method trains a model on the specified training data, and evaluates it
on the specified test data.
|
Modifier and Type | Field and Description |
---|---|
DataOptions |
TrainTest.TrainTestOptions.generalOptions |
Modifier and Type | Field and Description |
---|---|
DataOptions |
TrainTest.AllClassificationOptions.general |
DataOptions |
RunAll.RunAllOptions.general |
DataOptions |
ConfigurableTrainTest.ConfigurableTrainTestOptions.general |
Modifier and Type | Field and Description |
---|---|
DataOptions |
TrainTest.TrainTestOptions.general |
Modifier and Type | Field and Description |
---|---|
DataOptions |
TrainTest.TrainTestOptions.general |
Modifier and Type | Field and Description |
---|---|
DataOptions |
TrainTest.TrainTestOptions.general |
Modifier and Type | Field and Description |
---|---|
DataOptions |
TrainTest.TrainTestOptions.general |
Modifier and Type | Field and Description |
---|---|
DataOptions |
TrainTest.TrainTestOptions.general |
Modifier and Type | Field and Description |
---|---|
DataOptions |
TrainTest.TrainTestOptions.general |
Modifier and Type | Field and Description |
---|---|
DataOptions |
TrainTest.KMeansOptions.general |
Modifier and Type | Field and Description |
---|---|
DataOptions |
ConfigurableTrainTest.ConfigurableTrainTestOptions.general |
Modifier and Type | Field and Description |
---|---|
DataOptions |
TrainTest.LibLinearOptions.general |
Modifier and Type | Field and Description |
---|---|
DataOptions |
TrainTest.LibLinearOptions.general |
Modifier and Type | Field and Description |
---|---|
DataOptions |
TrainTest.DecisionTreeOptions.general |
Modifier and Type | Field and Description |
---|---|
DataOptions |
TrainTest.SGDOptions.general |
Modifier and Type | Field and Description |
---|---|
DataOptions |
TrainTest.LARSOptions.general |
Modifier and Type | Field and Description |
---|---|
DataOptions |
TrainTest.XGBoostOptions.general |
Copyright © 2015–2021 Oracle and/or its affiliates. All rights reserved.