Package org.tribuo.transform

package org.tribuo.transform

Provides infrastructure for applying transformations to a Dataset.

This package is the necessary infrastructure for transformations. The workflow is first to build a TransformationMap which represents the Transformations and the order that they should be applied to each Feature. This can be applied to a Dataset to produce a TransformerMap which contains a fitted set of Transformers which can be used to apply the transformation to any other Dataset (e.g., to apply the same transformation to training and test sets), or to be used at prediction time to stream data through.

It also provides a TransformTrainer which accepts a TransformationMap and an inner Trainer and produces a TransformedModel which automatically transforms it's input data at prediction time.

Related Packages

Package	Description
org.tribuo	Provides the core interfaces and classes for using Tribuo.
org.tribuo.transform.transformations	Provides implementations of standard transformations like binning, scaling, taking logs and exponents.

Class	Description
Transformation	An interface representing a class of transformations which can be applied to a feature.
TransformationMap	A carrier type for a set of transformations to be applied to a Dataset.
TransformationMap.TransformationList	A carrier type as OLCUT does not support nested generics.
TransformationProvenance	A tag interface for provenances in the transformation system.
TransformedModel<T extends Output<T>>	Wraps a Model with it's TransformerMap so all Examples are transformed appropriately before the model makes predictions.
Transformer	A fitted Transformation which can apply a transform to the input value.
TransformerMap	A collection of Transformers which can be applied to a Dataset or Example.
TransformerMap.TransformerMapProvenance	Provenance for TransformerMap.
TransformStatistics	An interface for the statistics that need to be collected for a specific Transformation on a single feature.
TransformTrainer<T extends Output<T>>	A Trainer which encapsulates another trainer plus a TransformationMap object to apply to each Dataset before training each Model.