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A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms
TLDR
a b s t r a c t The interest in nonparametric statistical analysis has grown recently in the field of computational intelligence. Expand
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KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework
TLDR
The aim of this paper is to present three new aspects of KEEL: KEEL-dataset, a data set repository which includes the data set partitions in theKEELformatandshowssomeresultsofalgorithmsinthesedatasets; some guidelines for including new algorithms in KEEL, helping the researcherstomaketheirmethodseasilyaccessibletootherauthorsandtocompare theresults of many approaches already included within the KEEL software. Expand
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An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics
TLDR
Training classifiers with datasets which suffer of imbalanced class distributions is an important problem in data mining. Expand
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Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power
TLDR
We present a case study which involves a set of techniques in classification tasks and we study the use of nonparametric statistical inference for analyzing the results obtained in an experiment design. Expand
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A study on the use of non-parametric tests for analyzing the evolutionary algorithms’ behaviour: a case study on the CEC’2005 Special Session on Real Parameter Optimization
TLDR
We focus our study on the use of statistical techniques in the analysis of evolutionary algorithms’ behaviour over optimization problems by using non-parametric test procedures. Expand
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An Extension on "Statistical Comparisons of Classifiers over Multiple Data Sets" for all Pairwise Comparisons
In a recently published paper in JMLR, Demˇ sar (2006) recommends a set of non-parametric statistical tests and procedures which can be safely used for comparing the performance of classifiers overExpand
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KEEL: a software tool to assess evolutionary algorithms for data mining problems
TLDR
This paper introduces a software tool named KEEL which is asoftware tool to assess evolutionary algorithms for Data Mining problems of various kinds including as regression, classification, unsupervised learning, etc. Expand
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Prototype Selection for Nearest Neighbor Classification: Taxonomy and Empirical Study
TLDR
The nearest neighbor classifier suffers from several drawbacks such as high storage requirements, low efficiency in classification response, and low noise tolerance. Expand
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A Survey of Discretization Techniques: Taxonomy and Empirical Analysis in Supervised Learning
TLDR
Discretization is an essential preprocessing technique used in many knowledge discovery and data mining tasks. Expand
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Self-labeled techniques for semi-supervised learning: taxonomy, software and empirical study
TLDR
Semi-supervised classification methods are suitable tools to tackle training sets with large amounts of unlabeled data and a small quantity of labeled data. Expand
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