PySeqLab: an open source Python package for sequence labeling and segmentation.

ABSTRACT:

Motivation

Text and genomic data are composed of sequential tokens, such as words and nucleotides that give rise to higher order syntactic constructs. In this work, we aim at providing a comprehensive Python library implementing conditional random fields (CRFs), a class of probabilistic graphical models, for robust prediction of these constructs from sequential data.

Results

Python Sequence Labeling (PySeqLab) is an open source package for performing supervised learning in structured prediction tasks. It implements CRFs models, that is discriminative models from (i) first-order to higher-order linear-chain CRFs, and from (ii) first-order to higher-order semi-Markov CRFs (semi-CRFs). Moreover, it provides multiple learning algorithms for estimating model parameters such as (i

SUBMITTER: Allam A 

PROVIDER: S-EPMC5872256 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature