Uses of Interface

Packages that use Output
Provides the core interfaces and classes for using Tribuo.
Provides classes and infrastructure for anomaly detection problems.
Provides classes and infrastructure for multiclass classification problems.
Provides core infrastructure for local model based explanations.
Provides an implementation of a linear chain CRF trained using Stochastic Gradient Descent.
Provides classes and infrastructure for working with clustering problems.
Provides base classes for using liblinear from Tribuo.
The base interface to LibSVM.
Provides a K-Nearest Neighbours implementation which works across all Tribuo Output types.
Provides the base classes for models trained with stochastic gradient descent.
Provides common functionality for building decision trees, irrespective of the predicted Output.
Provides abstract classes for interfacing with XGBoost abstracting away all the Output dependent parts.
Provides classes for loading in data from disk, processing it into examples, and splitting datasets for things like cross-validation and train-test splits.
Provides classes for processing columnar data and generating Examples.
Provides implementations of ResponseProcessor.
Provides classes which can load columnar data (using a RowProcessor) from a CSV (or other character delimited format) file.
Provides classes which can load columnar data (using a RowProcessor) from a SQL source.
Provides interfaces for converting text inputs into Features and Examples.
Provides implementations of text data processors.
Provides utility datasets which subsample or otherwise transform the wrapped dataset.
Simple data sources for ingesting or aggregating data.
Provides an interface for model prediction combinations, two base classes for ensemble models, a base class for ensemble excuses, and a Bagging implementation.
Evaluation base classes, along with code for train/test splits and cross validation.
This package contains the infrastructure classes for building evaluation metrics.
Provides the base interface and implementations of the Model hashing which obscures the feature names stored in a model.
Provides implementations of base classes and interfaces from org.tribuo.
This package contains the abstract implementation of an external model trained by something outside of Tribuo.
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 the ONNX Runtime.
Provides feature extraction implementations which use ONNX models.
Provides an interface to TensorFlow, allowing the training of non-sequential models using any supported Tribuo output type.
Provides an interface for working with TensorFlow sequence models, using Tribuo's SequenceModel abstraction.
Provides interop with JSON formatted data, along with tools for interacting with JSON provenance objects.
Provides a linear algebra system used for numerical operations in Tribuo.
Provides classes and infrastructure for working with multi-label classification problems.
Provides classes and infrastructure for regression problems with single or multiple output dimensions.
Reproducibility utility based on Tribuo's provenance objects.
Provides core classes for working with sequences of Examples.
Provides infrastructure for applying transformations to a Dataset.