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Rankings and Preferences
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This book examines in detail the correlation, more precisely the weighted correlation and applicationsinvolving rankings. A general applicationis the evaluation of methods to predict rankings. Others involverankings representing human preferences to infer user preferences; the use of weighted correlation with microarray data and those in the domain of time series. In this book we presentnewweightedcorrelation coefficients and new methods of weighted principal component analysis. We also introduce new methods of dimension reduction and clustering for time series data and describe some theoretical results on the weighted correlation coefficients in separate sections.
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