CACP: Classification Algorithms Comparison Pipeline

被引：3

作者：

Czmil, Sylwester ^{[1
]}

Kluska, Jacek ^{[1
]}

Czmil, Anna ^{[1
]}

机构：

[1] Rzeszow Univ Technol, Fac Elect & Comp Engn, Powstancow Warszawy 12, PL-35959 Rzeszow, Poland

来源：

SOFTWAREX | 2022年 / 19卷

关键词：

Supervised classification; Computational reproducibility; Classifier performance evaluation; Wilcoxon signed-rank test; CLASSIFIERS;

D O I：

10.1016/j.softx.2022.101134

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

This paper presents a Classification Algorithms Comparison Pipeline (CACP) for comparing newly developed classification algorithms in Python with other commonly used classifiers to evaluate classification performance, reproducibility, and statistical reliability. CACP simplifies the entire classifier evaluation process. Code examples and output results are explained and detailed to provide the basics of the module and give an overview of its capabilities. The code is available on GitHub under the MIT license. ?? 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

引用

页数：6

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