PLS in Data Mining and Data Integration

Data mining by means of projection methods such as PLS (projection to latent structures), and their extensions is discussed. The most common data analytical questions in data mining are covered, and illustrated with examples. (a) Clustering, i.e., finding and interpreting “natural” groups in the data (b) Classification and identification, e.g., biologically active compounds vs inactive (c) Quantitative relationships between different sets of variables, e.g., finding variables related to quality of a product, or related to time, seasonal or/and geographical change

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