RLScore: Regularized Least-Squares Learners

Tapio Pahikkala, Antti Airola; 17(221):1−5, 2016.

Abstract

RLScore is a Python open source module for kernel based machine learning. The library provides implementations of several regularized least-squares (RLS) type of learners. RLS methods for regression and classification, ranking, greedy feature selection, multi-task and zero-shot learning, and unsupervised classification are included. Matrix algebra based computational short-cuts are used to ensure efficiency of both training and cross-validation. A simple API and extensive tutorials allow for easy use of RLScore.

[abs][pdf][bib]    [code][cs.utu.fi]




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