000 | 02028cam a2200301 i 4500 | ||
---|---|---|---|
003 | CUTN | ||
005 | 20180912114806.0 | ||
008 | 140327s2014 maua b 001 0 eng | ||
020 | _a9788120350786 | ||
020 | _a9780262028189 (hardcover) | ||
020 | _a0262028182 (hardcover) | ||
041 | _aEnglish | ||
042 | _apcc | ||
082 | 0 | 0 |
_a006.31 _223 _bALP |
100 | 1 | _aAlpaydin, Ethem, | |
245 | 1 | 0 |
_aIntroduction to machine learning / _cEthem Alpaydin. |
250 | _aThird edition. | ||
300 |
_axxii, 613 pages : _billustrations ; _c24 cm. |
||
505 | 0 | _aIntroduction -- Supervised learning -- Bayesian decision theory -- Parametric methods -- Multivariate methods -- Dimensionality reduction -- Clustering -- Nonparametric methods -- Decision trees -- Linear discrimination -- Multilayer perceptrons -- Local models -- Kernel machines -- Graphical models -- Hidden markov models -- Bayesian estimation -- Combining multiple learners -- Reinforcement learning -- Design and analysis of machine learning experiments. | |
505 | 0 | _aPreface Notations 1. Introduction 2 Supervised Learning 3. Bayesian Decision Theory 4. Parametric Methods 5. Multivariate Methods 6. Dimensionality Reduction 7. Clustering 8. Nonparametric Methods 9. Decision Trees 10. Linear Discrimination 11. Multilayer Perceptrons 12. Local Models 13. Kernel Machines 14. Graphical Models 15. Hidden Markov Models 16. Bayesian Estimation 17. Combining Multiple Learners 18. Reinforcement Learning 19. Design and Analysis of Machine Learning Experiments A. Probability Index | |
650 | 0 | _aMachine learning. | |
942 |
_2ddc _cBOOKS |
||
100 | 1 | _eauthor. | |
490 | 0 | _aAdaptive computation and machine learning | |
504 | _aIncludes bibliographical references (page 203) and index. | ||
906 |
_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg |
||
999 |
_c25804 _d25804 |