000			02790nam a22005175i 4500
001			978-3-319-20010-1
003			DE-He213
005			20200421112549.0
007			cr nn 008mamaa
008			150715s2015 gw | s |||| 0|eng d
020			_a9783319200101 _9978-3-319-20010-1
024	7		_a10.1007/978-3-319-20010-1 _2doi
050		4	_aQ334-342
050		4	_aTJ210.2-211.495
072		7	_aUYQ _2bicssc
072		7	_aTJFM1 _2bicssc
072		7	_aCOM004000 _2bisacsh
082	0	4	_a006.3 _223
100	1		_aKubat, Miroslav. _eauthor.
245	1	3	_aAn Introduction to Machine Learning _h[electronic resource] / _cby Miroslav Kubat.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2015.
300			_aXIII, 291 p. 71 illus., 2 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aA Simple Machine-Learning Task -- Probabilities: Bayesian Classifiers -- Similarities: Nearest-Neighbor Classifiers -- Inter-Class Boundaries: Linear and Polynomial Classifiers -- Artificial Neural Networks -- Decision Trees -- Computational Learning Theory -- A Few Instructive Applications -- Induction of Voting Assemblies -- Some Practical Aspects to Know About -- Performance Evaluation.-Statistical Significance -- The Genetic Algorithm -- Reinforcement learning.
520			_aThis book presents basic ideas of machine learning in a way that is easy to understand, by providing hands-on practical advice, using simple examples, and motivating students with discussions of interesting applications. The main topics include Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, decision trees, neural networks, and support vector machines. Later chapters show how to combine these simple tools by way of "boosting," how to exploit them in more complicated domains, and how to deal with diverse advanced practical issues. One chapter is dedicated to the popular genetic algorithms.
650		0	_aComputer science.
650		0	_aInformation storage and retrieval.
650		0	_aArtificial intelligence.
650		0	_aComputer simulation.
650		0	_aPattern recognition.
650	1	4	_aComputer Science.
650	2	4	_aArtificial Intelligence (incl. Robotics).
650	2	4	_aSimulation and Modeling.
650	2	4	_aInformation Storage and Retrieval.
650	2	4	_aPattern Recognition.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783319200095
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-319-20010-1
912			_aZDB-2-SCS
942			_cEBK
999			_c58777 _d58777