Uses of Package
org.tribuo.classification
Package
Description
Provides classes and infrastructure for multiclass classification problems.
Provides simple baseline multiclass classifiers.
Provides implementations of decision trees for classification problems.
Provides internal implementation classes for classification decision trees.
Provides majority vote ensemble combiners for classification
along with an implementation of multiclass Adaboost.
Evaluation classes for multi-class classification.
Provides a multiclass data generator used for testing implementations, along with several synthetic data generators
for 2d binary classification problems to be used in demos or tutorials.
Provides a set of main methods for interacting with classification tasks.
Provides core infrastructure for local model based explanations.
Provides an implementation of LIME (Locally Interpretable Model Explanations).
Information theoretic feature selection algorithms.
Provides an interface to LibLinear-java for classification problems.
Provides an interface to LibSVM for classification problems.
Provides an implementation of multinomial naive bayes (i.e., naive bayes for non-negative count data).
Provides infrastructure for
SequenceModel
s which
emit Label
s at each step of the sequence.Provides a classification sequence data generator for smoke testing implementations.
Provides an implementation of Viterbi for generating structured outputs, which can sit on top of any
Label
based classification model.Provides an implementation of a linear chain CRF trained using Stochastic Gradient Descent.
Provides an implementation of a classification factorization machine using Stochastic Gradient Descent.
Provides a SGD implementation of a Kernel SVM using the Pegasos algorithm.
Provides an implementation of a classification linear model using Stochastic Gradient Descent.
Provides an interface to XGBoost for classification problems.
Provides a K-Nearest Neighbours implementation which works across
all Tribuo
Output
types.Code for uploading models to Oracle Cloud Infrastructure Data Science, and also for scoring models deployed
in Oracle Cloud Infrastructure Data Science.
This package contains a Tribuo wrapper around ONNX Runtime.
Provides an interface to TensorFlow, allowing the training of non-sequential models using any supported
Tribuo output type.
Provides classes and infrastructure for working with multi-label classification problems.
Provides implementations of binary relevance based multi-label classification
algorithms.
Provides a multi-label ensemble combiner that performs a (possibly
weighted) majority vote among each label independently, along with an
implementation of classifier chain ensembles.
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ClassDescriptionA tag interface for multi-class and multi-label classification tasks.An
ImmutableOutputInfo
object forLabel
s.An immutable multi-class classification label.A factory for making Label related classes.The base class for information about multi-class classification Labels.A mutableLabelInfo
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ClassDescriptionAn
Options
that can produce a classificationTrainer
based on the provided arguments.An immutable multi-class classification label. -
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ClassDescriptionA tag interface for multi-class and multi-label classification tasks.An immutable multi-class classification label.
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ClassDescriptionAn immutable multi-class classification label.A factory for making Label related classes.
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ClassDescriptionAn
Options
that can produce a classificationTrainer
based on the provided arguments.An immutable multi-class classification label. -
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ClassDescriptionAn
Options
that can produce a classificationTrainer
based on the provided arguments.An immutable multi-class classification label. -
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ClassDescriptionAn
Options
that can produce a classificationTrainer
based on the provided arguments.An immutable multi-class classification label. -
ClassDescriptionAn
Options
that can produce a classificationTrainer
based on the provided arguments.An immutable multi-class classification label. -
ClassDescriptionAn
Options
that can produce a classificationTrainer
based on the provided arguments.An immutable multi-class classification label. -
ClassDescriptionAn
Options
that can produce a classificationTrainer
based on the provided arguments.An immutable multi-class classification label. -
ClassDescriptionAn
Options
that can produce a classificationTrainer
based on the provided arguments.An immutable multi-class classification label. -
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ClassDescriptionA tag interface for multi-class and multi-label classification tasks.An immutable multi-class classification label.
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