Nonparametric Statistical Analysis of Machine Learning Algorithms for Regression Problems

被引：0

作者：

Graczyk, Magdalena ^{[1
]}

Lasota, Tadeusz ^{[2
]}

Telec, Zbigniew ^{[1
]}

Trawinski, Bogdan ^{[1
]}

机构：

[1] Wroclaw Univ Technol, Inst Informat, Wybrzeze Wyspianskiego 27, PL-50370 Wroclaw, Poland

[2] Wroclaw Univ Environm & Life Sci, Dept Spatial Management, PL-50370 Wroclaw, Poland

来源：

KNOWLEDGE-BASED AND INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, PT I | 2010年 / 6276卷

关键词：

machine learning; statistical tests; statistical regression; decision trees; neural networks; KEEL; MODELS; CLASSIFIERS; TESTS; KEEL;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Several experiments aimed to apply recently proposed statistical procedures which are recommended for analysing multiple Ixn and nxn comparisons of machine learning algorithms were conducted. 11 regression algorithms comprising 5 deterministic and 6 neural network ones implemented in the data mining system KEEL were employed. All experiments were performed wing 29 benchmark datasets for regression. The investigation proved the usefulness and strength of multiple comparison statistical procedures to analyse and select machine learning algorithms.

引用

页码：111 / +

页数：3

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