the art and science of algorithms that make sense of data Flach, Peter A. creator text bibliography enk Cambridge New York Cambridge University Press 2012 monographic eng

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xvii, 396 p. : col. ill. ; 25 cm. 'Machine Learning' brings together all the state-of-the-art methods for making sense of data. With hundreds of worked examples and explanatory figures, it explains the principles behind these methods in an intuitive yet precise manner and will appeal to novice and experienced readers alike. 1. The ingredients of machine learning -- 2. Binary classification and related tasks -- 3. Beyond binary classification -- 4. Concept learning -- 5. Tree models -- 6. Rule models -- 7. Linear models -- 8. Distance-based models -- 9. Probabilistic models -- 10. Features -- 11. Model ensembles -- 12. Machine learning experiments -- Epilogue: where to go from here. Peter Flach. Includes bibliographical references (p. 367-381) and index. Machine learning Textbooks Apprentissage automatique Manuels scolaires Q325.5 .F53 2012 006.31 9781107096394 (hbk.) 1107096391 (hbk.) 9781107422223 (pbk.) 1107422221 (pbk.) 2012289353 UKMGB 130131 20170105102416.0 17609682 eng