01900cam a22003377a 45000010009000000050017000090080041000260100015000670200025000820200022001070200025001290200022001540400093001760820020002691000027002892450098003162500025004142600068004393000052005075000028005595000024005875040031006115050334006425200296009766500039012726530033013116550024013449420020013689990017013889520157014051760968220141216150759.0130131r20122014xxkadk fr2b  f001 0 eng d  a2012289353  a9781107096394 (hbk.)  a1107096391 (hbk.)  a9781107422223 (pbk.)  a1107422221 (pbk.)  aUKMGBbengcUKMGBdBTCTAdOCLCOdBDXdYDXCPdCDXdZWZdEYMdTEFdJHEdMUUdDLCdEG-ScBUE00a006.31222bFLA1 aFlach, Peter A.93694510aMachine learning :bthe art and science of algorithms that make sense of data /cPeter Flach.  a1st ed.,breprinted.  aCambridge, United Kingdom :bCambridge University Press,c2012.  axvii, 396 p. :bcharts, forms, tables ;c25 cm.  aReprint of the 2012 ed.  aIndex : p. 383-396.  aBibliography : p. 367-381.0 a1. The ingredients of machine learning-2. Binary classification and related tasks-3. Beyond binary classification-4. Concept learning-5. Tree models-6. Rule models-7. Linear models-8. Distance-based models-9. Probabilistic models-10. Features-11. Model ensembles-12. Machine learning experiments-Epilogue : where to go from here.3 a'Machine Learning' brings together all the state-of-the-art methods for making sense of data. With hundreds of worked examples and explanatory figures, it explains the principles behind these methods in an intuitive yet precise manner and will appeal to novice and experienced readers alike. 0aMachine learningvTextbooks936946  bENGELCbCOMSCIcDecember2014  vreading book934232  2ddck006.31 FLA  c18786d18758  00102ddc40708BaccahaMAINbMAINcLOWd2014-12-16epurchaseg376.00h21291l2m16o006.31 FLAp000037201r2025-07-15 00:00:00s2019-04-09v468.00yBB