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Machine learning : the art and science of algorithms that make sense of data / Peter Flach.

By: Flach, Peter A [aut]Material type: TextTextLanguage: English Publisher: Cambridge : Cambridge University Press, 2012Description: xvii, 396 pages illustrations 25 cmContent type: text Media type: unmediated Carrier type: volumeISBN: 9781107096394; 1107096391; 9781107422223; 1107422221Subject(s): Maskininlärning | Machine learning -- Textbooks | Algorithmes | Programmation informatique | Machine learning | Machine learningGenre/Form: Textbooks.DDC classification: 006.31 LOC classification: Q325.5 | .F53 2012Other classification: Pud
Contents:
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.
Abstract: '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.
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Book (loan) Gräsvik
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Book (loan) Gräsvik
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Book (loan) Gräsvik
006.3 Checked out 2023-06-07 080047624376
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Referens
006.3 Available 080047624375
Book (loan) Gräsvik
006.3 Available 080041486801

Includes bibliographical references (pages 367-381) and index.

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.

'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.

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