000 | 02790nam a22005175i 4500 | ||
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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 |
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024 | 7 |
_a10.1007/978-3-319-20010-1 _2doi |
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050 | 4 | _aQ334-342 | |
050 | 4 | _aTJ210.2-211.495 | |
072 | 7 |
_aUYQ _2bicssc |
|
072 | 7 |
_aTJFM1 _2bicssc |
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072 | 7 |
_aCOM004000 _2bisacsh |
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082 | 0 | 4 |
_a006.3 _223 |
100 | 1 |
_aKubat, Miroslav. _eauthor. |
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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. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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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 |