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Predictive modelling in high-dimensional data: prior domain knowledge-based approaches

Maciejewski H.

This book is devoted to the problem of predictive modelling based on high-dimensional data, focusing mainly on the cases where the number of training samples Is substantially smaller than the number of features. Analysis of such data is becoming increasingly important in many areas of science and technology, including bioinformatics, image analysis or text mining.

The major challenge in the analysis of such data is the selection of stable, relevant features for class prediction. As a remedy to this, in this book we develop methods which allow us to include a priori domain knowledge on relationships among features. This approach can stabilize feature selection and improve classification.

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