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Zdzisław Pawlak: Man, Creator and Innovator ofComputer Sciences Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Introducing NRough Framework

Author : Sebastian Widz

Published in: Rough Sets

Publisher: Springer International Publishing

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Abstract

In this article we present the new machine learning framework called NRough. It is focused on rough set based algorithms for feature selection and classification i.e. computation of various types of decision reducts, bireducts, decision reduct ensembles and rough set inspired decision rule induction. Moreover, the framework contains other routines and algorithms for supervised and unsupervised learning. NRough is written in C# and compliant with .NET Common Language Specification (CLS). Its architecture allows easy extendability and integration.

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previous chapter Hardware Supported Rule-Based Classification on Big Datasets
Appendix
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Metadata
Title
Introducing NRough Framework
Author
Sebastian Widz
Copyright Year
2017
Book
Rough Sets

Print ISBN: 978-3-319-60836-5

Electronic ISBN: 978-3-319-60837-2

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-60837-2_53

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