Matches in Library of Congress for { <http://lccn.loc.gov/2010045223> ?p ?o. }
Showing items 1 to 34 of
34
with 100 items per page.
- 2010045223 contributor B11790890.
- 2010045223 contributor B11790891.
- 2010045223 created "c2011.".
- 2010045223 date "2011".
- 2010045223 date "c2011.".
- 2010045223 dateCopyrighted "c2011.".
- 2010045223 description "Includes bibliographical references and indexes.".
- 2010045223 description "Introduction: Classification, Learning, Features, and Applications -- Probability -- Probability Densities -- The Pattern Recognition Problem -- The Optimal Bayes Decision Rule -- Learning from Examples -- The Nearest Neighbor Rule -- Kernel Rules -- Neural Networks: Perceptrons -- Multilayer Networks -- PAC Learning -- VC Dimension -- Infinite VC Dimension -- The Function Estimation Problem -- Learning Function Estimation -- Simplicity -- Support Vector Machines -- Boosting -- Bibliography.".
- 2010045223 extent "xiv, 209 p. :".
- 2010045223 identifier "0470641835 (cloth)".
- 2010045223 identifier "1118023439".
- 2010045223 identifier "1118023463".
- 2010045223 identifier "1118023471".
- 2010045223 identifier "9780470641835 (cloth)".
- 2010045223 identifier "9781118023433".
- 2010045223 identifier "9781118023464".
- 2010045223 identifier "9781118023471".
- 2010045223 identifier F?func=service&doc_library=BVB01&doc_number=024567239&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.
- 2010045223 identifier 2010045223-b.html.
- 2010045223 identifier 2010045223-d.html.
- 2010045223 identifier 2010045223-t.html.
- 2010045223 isPartOf "Wiley series in probability and statistics".
- 2010045223 isPartOf "Wiley series in probability and statistics.".
- 2010045223 issued "2011".
- 2010045223 issued "c2011.".
- 2010045223 language "eng".
- 2010045223 publisher "Hoboken, N.J. : Wiley,".
- 2010045223 subject "006.3/1 22".
- 2010045223 subject "Machine learning Statistical methods.".
- 2010045223 subject "Pattern recognition systems.".
- 2010045223 subject "Q325.5 .K85 2011".
- 2010045223 tableOfContents "Introduction: Classification, Learning, Features, and Applications -- Probability -- Probability Densities -- The Pattern Recognition Problem -- The Optimal Bayes Decision Rule -- Learning from Examples -- The Nearest Neighbor Rule -- Kernel Rules -- Neural Networks: Perceptrons -- Multilayer Networks -- PAC Learning -- VC Dimension -- Infinite VC Dimension -- The Function Estimation Problem -- Learning Function Estimation -- Simplicity -- Support Vector Machines -- Boosting -- Bibliography.".
- 2010045223 title "An elementary introduction to statistical learning theory / Sanjeev Kulkarni, Gilbert Harman.".
- 2010045223 type "text".