Description:

stroll (STRuctured Output Learning Library) is a library for Structured Output Learning. For now it only supports various training and prediction approaches for Conditional Random Fields (CRF), but support for Structural SVMs is planned for the near future.

Features: Supports general (possibly intractable) factor graphs. Easy to use. We provide Python bindings for stroll that simplify the development with stroll considerably. Most of the inference algorithms implemented by libDAI can be used with smaller modifications for both, training and prediction with CRFs. Implements the spanning tree based training approach for CRFs described in our AISTATS paper

Changes to previous version:

Initial Announcement on mloss.org.

BibTeX Entry: Download

Corresponding Paper BibTeX Entry: Download

Supported Operating Systems: Linux

Data Formats: None

Tags: Structure Learning, Structured Outputs, Classification, Multilabel, Approximate Inference, Approximate Learning

Archive: download here

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