Package org.tribuo

package org.tribuo

Provides the core interfaces and classes for using Tribuo.

This package contains a dataset class, several classes which represent datapoints (subclasses of Example), the canonical Feature class, interfaces for training models and working with outputs.

Related Packages

Package	Description
org.tribuo.anomaly	Provides classes and infrastructure for anomaly detection problems.
org.tribuo.classification	Provides classes and infrastructure for multiclass classification problems.
org.tribuo.clustering	Provides classes and infrastructure for working with clustering problems.
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.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.impl	Provides implementations of base classes and interfaces from org.tribuo.
org.tribuo.interop	This package contains the abstract implementation of an external model trained by something outside of Tribuo.
org.tribuo.json	Provides interop with JSON formatted data, along with tools for interacting with JSON provenance objects.
org.tribuo.math	Contains the implementation of Tribuo's math library, it's gradient descent optimisers, kernels and a set of math related utils.
org.tribuo.multilabel	Provides classes and infrastructure for working with multi-label classification problems.
org.tribuo.provenance	Provides Tribuo specific infrastructure for the Provenance system which tracks models and datasets.
org.tribuo.regression	Provides classes and infrastructure for regression problems with single or multiple output dimensions.
org.tribuo.sequence	Provides core classes for working with sequences of Examples.
org.tribuo.tests	This package provides helper classes for Tribuo's unit tests.
org.tribuo.transform	Provides infrastructure for applying transformations to a Dataset.
org.tribuo.util	Provides utilities which don't have other Tribuo dependencies.

Class	Description
CategoricalIDInfo	Same as a CategoricalInfo, but with an additional int id field.
CategoricalInfo	Stores information about Categorical features.
ConfigurableDataSource<T extends Output<T>>	It's a DataSource that's also Configurable.
Dataset<T extends Output<T>>	A class for sets of data, which are used to train and evaluate classifiers.
DataSource<T extends Output<T>>	A interface for things that can be given to a Dataset's constructor.
Example<T extends Output<T>>	An example used for training and evaluation.
Excuse<T extends Output<T>>	Holds an Example, a Prediction and a Map from String to List of Pairs that contains the per output explanation.
Feature	A class for features.
FeatureMap	A map from Strings to VariableInfo objects storing information about a feature.
ImmutableDataset<T extends Output<T>>	This is a Dataset which has an ImmutableFeatureMap to store the feature information.
ImmutableFeatureMap	ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
ImmutableOutputInfo<T extends Output<T>>	An OutputInfo that is fixed, and contains an id number for each valid output.
IncrementalTrainer<T extends Output<T>, U extends Model<T>>	An interface for incremental training of Models.
Model<T extends Output<T>>	A prediction model, which is used to predict outputs for unseen instances.
ModelExplorer	A command line interface for loading in models and inspecting their feature and output spaces.
ModelExplorer.ModelExplorerOptions	CLI options for ModelExplorer.
MutableDataset<T extends Output<T>>	A MutableDataset is a Dataset with a MutableFeatureMap which grows over time.
MutableFeatureMap	A feature map that can record new feature value observations.
MutableOutputInfo<T extends Output<T>>	A mutable OutputInfo that can record observed output values.
Output<T extends Output<T>>	Output is the root interface for the supported prediction types.
OutputFactory<T extends Output<T>>	An interface associated with a specific Output, which can generate the appropriate Output subclass, and OutputInfo subclass.
OutputInfo<T extends Output<T>>	Tracks relevant properties of the appropriate Output subclass.
Prediction<T extends Output<T>>	A prediction made by a Model.
RealIDInfo	Same as a RealInfo, but with an additional int id field.
RealInfo	Stores information about real valued features.
SkeletalVariableInfo	Contains information about a feature and can be stored in the feature map in a Dataset.
SparseModel<T extends Output<T>>	A model which uses a subset of the features it knows about to make predictions.
SparseTrainer<T extends Output<T>>	Denotes this trainer emits a SparseModel.
Trainer<T extends Output<T>>	An interface for things that can train predictive models.
Tribuo	This class stores the current Tribuo version, along with other compile time information.
VariableIDInfo	Adds an id number to a VariableInfo.
VariableInfo	A VariableInfo subclass contains information about a feature and its observed values.
WeightedExamples	Tag interface denoting that a Trainer can use example weights.