Alpaydin, Ethem. <br/><br/>
Introduction to machine learning  
Ethem Alpaydın. 
 - New Delhi :  Prentice-Hall of India,  c2004. [reprinted 2006] 
 - xxx, 415 p. :  ill. , figs.;  24 cm. 
<br/><br/>Includes bibliographical references and index. 
<br/><br/> Introduction --   Supervised learning --   Bayesian decision theory --   Parametric methods --   Multivariate methods --   Dimensionality reduction --   Clustering --   Nonparametric methods --   Decision trees --   Linear discrimination --   Multilayer perceptrons --   Local models --   Hidden Markov models --   Assessing and comparing classification algorithms --   Combining multiple learners --   Reinforcement learning --   Probability.  1.  2.  3.  4.  5.  6.  7.  8.  9.  10.  11.  12.  13.  14.  15.  16.  A. 
<br/><br/> "This book can be used by advanced undergraduates and graduate students who have completed courses in computer programming, probability, calculus, and linear algebra. It will also be of interest to engineers in the field who are concerned with the application of machine learning methods."--BOOK JACKET. 
<br/><br/>
<br/><br/><label>ISBN: </label>0262012111 
<br/><br/><label>LCCN: </label>2004109627 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Machine learning.
<br/><br/><label>LC Class. No.: </label>Q325.5  / .A473 2004 
<br/><br/><label>Dewey Class. No.: </label>006.31/ A456i