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