Neural networks: a systematic introduction
Neural networks: a systematic introduction
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
Working Set Selection Using Second Order Information for Training Support Vector Machines
The Journal of Machine Learning Research
Biostatistical Analysis (5th Edition)
Biostatistical Analysis (5th Edition)
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
A lot of randomness is hiding in accuracy
Engineering Applications of Artificial Intelligence
Classifier fitness based on accuracy
Evolutionary Computation
Handbook of Parametric and Nonparametric Statistical Procedures
Handbook of Parametric and Nonparametric Statistical Procedures
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
Natural Encoding for Evolutionary Supervised Learning
IEEE Transactions on Evolutionary Computation
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The experimental analysis on the performance of a proposed method is a crucial and necessary task to carry out in a research. In this contribution we focus on the use of statistical inference for analyzing the results obtained in a design of experiment within the field of computational intelligence. We present some studies involving a set of techniques in different topics which can be used for doing a rigorous comparison among the algorithms studied in an experimental comparison.Particularly, we study whether the sample of results from multiple trials obtained by the run of several algorithms checks the required conditions for being analyzed through parametric tests. In most of the cases, the results indicate that the fulfillment of these conditions are problem dependent and indefinite, which justifies the need of using nonparametric statistics in the experimental analysis. We show a case study which illustrates the use of nonparametric tests and finally we give some guidelines on the use of nonparametric statistical tests.