000			02090nam a2200289Ia 4500
003			OSt
005			20251224095833.0
008			220909b |||||||| |||| 00| 0 eng d
020			_a9789814590075
037			_cTextual
040			_aCSL _beng _cCSL
041			_aeng
084			_aD65,8(B),27, Q5 _qCSL
100			_aRokach, Lior _eauthor. _9859168
245		0	_aData Mining with Decision Trees _b: Theory and Applicatios
250			_a2nd
260			_aSingapore: _bWorld Scientifc, _c2015.
300			_axxi, 305p. _b: ill.
500			_aBibliography 273-302p.; Index 303-305p.
520			_aDecision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining; it is the science of exploring large and complex bodies of data in order to discover useful patterns. Decision tree learning continues to evolve over time. Existing methods are constantly being improved and new methods introduced.This 2nd Edition is dedicated entirely to the field of decision trees in data mining; to cover all aspects of this important technique, as well as improved or new methods and techniques developed after the publication of our first edition. In this new edition, all chapters have been revised and new topics brought in. New topics include Cost-Sensitive Active Learning, Learning with Uncertain and Imbalanced Data, Using Decision Trees beyond Classification Tasks, Privacy Preserving Decision Tree Learning, Lessons Learned from Comparative Studies, and Learning Decision Trees for Big Data. A walk-through guide to existing open-source data mining software is also included in this edition.This book invites readers to explore the many benefits in data mining that decision trees offer:
650			_a Fuzzy decision trees _9859169
650			_a Pruning trees _9859170
650			_aTraining decision trees _9859171
700			_aMaimon, Oded _eauthor. _9859172
942			_hD65,8(B),27, Q5 _cTEXL _2CC _e2nd _n0
999			_c15865 _d15865