Introducing NRough Framework

被引：3
|
作者：
Widz, Sebastian [1 ]
机构：
[1] Polish Acad Sci, Syst Res Inst, Ul Newelska 6, PL-01447 Warsaw, Poland
来源：
ROUGH SETS | 2017年 / 10313卷
关键词：
Rough sets; Approximate decision reducts; Bireducts; NET; C#; ROUGH; RULES;
D O I：
10.1007/978-3-319-60837-2_53
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：669 / 689
页数：21
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