Uses of Package
org.tribuo.provenance

Packages that use org.tribuo.provenance
Package
Description
org.tribuo
Provides the core interfaces and classes for using Tribuo.
org.tribuo.anomaly
Provides classes and infrastructure for anomaly detection problems.
org.tribuo.anomaly.evaluation
Evaluation classes for anomaly detection.
org.tribuo.anomaly.liblinear
Provides an interface to LibLinear-java for anomaly detection problems.
org.tribuo.anomaly.libsvm
Provides an interface to LibSVM for anomaly detection problems.
org.tribuo.classification
Provides classes and infrastructure for multiclass classification problems.
org.tribuo.classification.baseline
Provides simple baseline multiclass classifiers.
org.tribuo.classification.dtree
Provides implementations of decision trees for classification problems.
org.tribuo.classification.ensemble
Provides majority vote ensemble combiners for classification along with an implementation of multiclass Adaboost.
org.tribuo.classification.evaluation
Evaluation classes for multi-class classification.
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.sequence
Provides infrastructure for SequenceModels which emit Labels at each step of the sequence.
org.tribuo.classification.sequence.viterbi
Provides an implementation of Viterbi for generating structured outputs, which can sit on top of any Label based classification model.
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.clustering
Provides classes and infrastructure for working with clustering problems.
org.tribuo.clustering.evaluation
Evaluation classes for clustering.
org.tribuo.clustering.kmeans
Provides a multithreaded implementation of K-Means, with a configurable distance function.
org.tribuo.common.liblinear
Provides base classes for using liblinear from Tribuo.
org.tribuo.common.libsvm
The base interface to LibSVM.
org.tribuo.common.nearest
Provides a K-Nearest Neighbours implementation which works across all Tribuo Output types.
org.tribuo.common.sgd
Provides the base classes for models trained with stochastic gradient descent.
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.data.csv
Provides classes which can load columnar data (using a RowProcessor) from a CSV (or other character delimited format) file.
org.tribuo.data.sql
Provides classes which can load columnar data (using a RowProcessor) from a SQL source.
org.tribuo.data.text
Provides interfaces for converting text inputs into Features and Examples.
org.tribuo.data.text.impl
Provides implementations of text data processors.
org.tribuo.dataset
Provides utility datasets which subsample or otherwise transform the wrapped dataset.
org.tribuo.datasource
Simple data sources for ingesting or aggregating data.
org.tribuo.ensemble
Provides an interface for model prediction combinations, two base classes for ensemble models, a base class for ensemble excuses, and a Bagging implementation.
org.tribuo.evaluation
Evaluation base classes, along with code for train/test splits and cross validation.
org.tribuo.hash
Provides the base interface and implementations of the Model hashing which obscures the feature names stored in a model.
org.tribuo.interop
This package contains the abstract implementation of an external model trained by something outside of Tribuo.
org.tribuo.interop.onnx
This package contains a Tribuo wrapper around the ONNX Runtime.
org.tribuo.interop.tensorflow
Provides an interface to TensorFlow, allowing the training of non-sequential models using any supported Tribuo output type.
org.tribuo.interop.tensorflow.sequence
Provides an interface for working with TensorFlow sequence models, using Tribuo's SequenceModel abstraction.
org.tribuo.json
Provides interop with JSON formatted data, along with tools for interacting with JSON provenance objects.
org.tribuo.multilabel
Provides classes and infrastructure for working with multi-label classification problems.
org.tribuo.multilabel.baseline
Provides an implementation of independent multi-label classification that wraps a Label Trainer and uses it to make independent predictions of each label.
org.tribuo.multilabel.evaluation
Evaluation classes for multi-label classification using MultiLabel.
org.tribuo.multilabel.sgd.linear
Provides an implementation of a multi-label classification linear model using Stochastic Gradient Descent.
org.tribuo.provenance
Provides Tribuo specific infrastructure for the Provenance system which tracks models and datasets.
org.tribuo.provenance.impl
Provides internal implementations for empty provenance classes and TrainerProvenance.
org.tribuo.regression
Provides classes and infrastructure for regression problems with single or multiple output dimensions.
org.tribuo.regression.baseline
Provides simple baseline regression predictors.
org.tribuo.regression.evaluation
Evaluation classes for single or multi-dimensional regression.
org.tribuo.regression.example
Provides some example regression data generators for testing implementations.
org.tribuo.regression.impl
Provides skeletal implementations of Regressor Trainer that can wrap a single dimension trainer/model and produce one prediction per dimension independently.
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.linear
Provides an implementation of linear regression using Stochastic Gradient Descent.
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.
org.tribuo.sequence
Provides core classes for working with sequences of Examples.
org.tribuo.transform
Provides infrastructure for applying transformations to a Dataset.