16 126 809 książek w 175 językach
Jednak się nie przyda? Nic nie szkodzi! U nas możesz zwrócić towar do 30 dni
Bon prezentowy to zawsze dobry pomysł. Obdarowany może za bon prezentowy wybrać cokolwiek z naszej oferty.
30 dni na zwrot towaru
The field of machine learning has matured to the point where many sophisticated learning approaches can be applied to practical applications. Thus it is of critical importance that researchers have the proper tools to evaluate learning approaches and understand the underlying issues. This book examines various aspects of the evaluation process with an emphasis on classification algorithms. The authors describe several techniques for classifier performance assessment, error estimation and resampling, obtaining statistical significance as well as selecting appropriate domains for evaluation. They also present a unified evaluation framework and highlight how different components of evaluation are both significantly interrelated and interdependent. The techniques presented in the book are illustrated using R and WEKA, facilitating better practical insight as well as implementation. Aimed at researchers in the theory and applications of machine learning, this book offers a solid basis for conducting performance evaluations of algorithms in practical settings.