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008 170213s2015 gw | s |||| 0|eng d
020 _a9783319253886
_9978-3-319-25388-6
024 7 _a10.1007/978-3-319-25388-6
_2doi
035 _ato000560951
040 _aSpringer
_cSpringer
_dRU-ToGU
050 4 _aQA273.A1-274.9
050 4 _aQA274-274.9
072 7 _aPBT
_2bicssc
072 7 _aPBWL
_2bicssc
072 7 _aMAT029000
_2bisacsh
082 0 4 _a519.2
_223
100 1 _aBiau, Gérard.
_eauthor.
_9467717
245 1 0 _aLectures on the Nearest Neighbor Method
_helectronic resource
_cby Gérard Biau, Luc Devroye.
250 _a1st ed. 2015.
260 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2015.
300 _aIX, 290 p. 4 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aSpringer Series in the Data Sciences,
_x2365-5674
505 0 _aPart I: Density Estimation -- Order Statistics and Nearest Neighbors -- The Expected Nearest Neighbor Distance -- The k-nearest Neighbor Density Estimate -- Uniform Consistency -- Weighted k-nearest neighbor density estimates.- Local Behavior -- Entropy Estimation -- Part II: Regression Estimation -- The Nearest Neighbor Regression Function Estimate -- The 1-nearest Neighbor Regression Function Estimate -- LP-consistency and Stone's Theorem -- Pointwise Consistency -- Uniform Consistency -- Advanced Properties of Uniform Order Statistics -- Rates of Convergence -- Regression: The Noisless Case -- The Choice of a Nearest Neighbor Estimate -- Part III: Supervised Classification -- Basics of Classification -- The 1-nearest Neighbor Classification Rule -- The Nearest Neighbor Classification Rule. Appendix -- Index.
520 _aThis text presents a wide-ranging and rigorous overview of nearest neighbor methods, one of the most important paradigms in machine learning. Now in one self-contained volume, this book systematically covers key statistical, probabilistic, combinatorial and geometric ideas for understanding, analyzing and developing nearest neighbor methods. Gérard Biau is a professor at Université Pierre et Marie Curie (Paris). Luc Devroye is a professor at the School of Computer Science at McGill University (Montreal).   .
650 0 _amathematics.
_9566183
650 0 _aPattern Recognition.
_9304129
650 0 _aProbabilities.
_9295556
650 0 _aStatistics.
_9124796
650 1 4 _aMathematics.
_9566184
650 2 4 _aProbability Theory and Stochastic Processes.
_9303734
650 2 4 _aPattern Recognition.
_9304129
650 2 4 _aStatistics and Computing/Statistics Programs.
_9303277
700 1 _aDevroye, Luc.
_eauthor.
_9467718
710 2 _aSpringerLink (Online service)
_9143950
773 0 _tSpringer eBooks
830 0 _aSpringer Series in the Data Sciences,
_9467719
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-25388-6
912 _aZDB-2-SMA
999 _c415335