| Package | Description |
|---|---|
| org.tribuo.classification.dtree |
Provides implementations of decision trees 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.crf |
Provides an implementation of a linear chain CRF trained using Stochastic Gradient Descent.
|
| org.tribuo.classification.sgd.kernel |
Provides a SGD implementation of a Kernel SVM using the Pegasos algorithm.
|
| org.tribuo.classification.sgd.linear |
Provides an implementation of a classification linear model using Stochastic Gradient Descent.
|
| org.tribuo.classification.xgboost |
Provides an interface to XGBoost for classification problems.
|
| org.tribuo.common.tree |
Provides common functionality for building decision trees, irrespective
of the predicted
Output. |
| org.tribuo.common.xgboost |
Provides abstract classes for interfacing with XGBoost abstracting away all the
Output
dependent parts. |
| org.tribuo.regression.rtree |
Provides an implementation of decision trees for regression problems.
|
| 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 | Class and Description |
|---|---|
class |
CARTClassificationTrainer
A
Trainer that uses an approximation of the CART algorithm to build a decision tree. |
| Modifier and Type | Class and Description |
|---|---|
class |
MultinomialNaiveBayesTrainer
A
Trainer which trains a multinomial Naive Bayes model with Laplace smoothing. |
| Modifier and Type | Class and Description |
|---|---|
class |
CRFTrainer
A trainer for CRFs using SGD.
|
| Modifier and Type | Class and Description |
|---|---|
class |
KernelSVMTrainer
A trainer for a kernelised model using the Pegasos optimiser.
|
| Modifier and Type | Class and Description |
|---|---|
class |
LinearSGDTrainer
A trainer for a linear model which uses SGD.
|
class |
LogisticRegressionTrainer
A logistic regression trainer that uses a reasonable objective, optimiser,
number of epochs and minibatch size.
|
| Modifier and Type | Class and Description |
|---|---|
class |
XGBoostClassificationTrainer
A
Trainer which wraps the XGBoost training procedure. |
| Modifier and Type | Interface and Description |
|---|---|
interface |
DecisionTreeTrainer<T extends Output<T>>
A tag interface for a
Trainer so the random forests trainer can check if it's actually a tree. |
| Modifier and Type | Class and Description |
|---|---|
class |
AbstractCARTTrainer<T extends Output<T>>
Base class for
Trainer's that use an approximation of the CART algorithm to build a decision tree. |
| Modifier and Type | Class and Description |
|---|---|
class |
XGBoostTrainer<T extends Output<T>>
A
Trainer which wraps the XGBoost training procedure. |
| Modifier and Type | Class and Description |
|---|---|
class |
CARTJointRegressionTrainer
A
Trainer that uses an approximation of the CART algorithm to build a decision tree. |
class |
CARTRegressionTrainer
A
Trainer that uses an approximation of the CART algorithm to build a decision tree. |
| Modifier and Type | Class and Description |
|---|---|
class |
LARSLassoTrainer
A trainer for a lasso linear regression model which uses LARS to construct the model.
|
class |
LARSTrainer
A trainer for a linear regression model which uses least angle regression.
|
class |
SLMTrainer
A trainer for a sparse linear regression model.
|
| Modifier and Type | Class and Description |
|---|---|
class |
XGBoostRegressionTrainer
A
Trainer which wraps the XGBoost training procedure. |
Copyright © 2015–2021 Oracle and/or its affiliates. All rights reserved.