000			03227nam a22005535i 4500
001			978-3-319-24211-8
003			DE-He213
005			20200421111159.0
007			cr nn 008mamaa
008			160429s2016 gw | s |||| 0|eng d
020			_a9783319242118 _9978-3-319-24211-8
024	7		_a10.1007/978-3-319-24211-8 _2doi
050		4	_aTK1-9971
072		7	_aTJK _2bicssc
072		7	_aTEC041000 _2bisacsh
082	0	4	_a621.382 _223
245	1	0	_aUnsupervised Learning Algorithms _h[electronic resource] / _cedited by M. Emre Celebi, Kemal Aydin.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2016.
300			_aX, 558 p. 160 illus., 101 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		_aIntroduction -- Feature Construction -- Feature Extraction -- Feature Selection -- Association Rule Learning -- Clustering -- Anomaly/Novelty/Outlier Detection -- Evaluation of Unsupervised Learning -- Applications -- Conclusion.
520			_aThis book summarizes the state-of-the-art in unsupervised learning. The contributors discuss how with the proliferation of massive amounts of unlabeled data, unsupervised learning algorithms, which can automatically discover interesting and useful patterns in such data, have gained popularity among researchers and practitioners. The authors outline how these algorithms have found numerous applications including pattern recognition, market basket analysis, web mining, social network analysis, information retrieval, recommender systems, market research, intrusion detection, and fraud detection. They present how the difficulty of developing theoretically sound approaches that are amenable to objective evaluation have resulted in the proposal of numerous unsupervised learning algorithms over the past half-century. The intended audience includes researchers and practitioners who are increasingly using unsupervised learning algorithms to analyze their data. Topics of interest include anomaly detection, clustering, feature extraction, and applications of unsupervised learning. Each chapter is contributed by a leading expert in the field.
650		0	_aEngineering.
650		0	_aComputer communication systems.
650		0	_aData mining.
650		0	_aArtificial intelligence.
650		0	_aPattern recognition.
650		0	_aComputational intelligence.
650		0	_aElectrical engineering.
650	1	4	_aEngineering.
650	2	4	_aCommunications Engineering, Networks.
650	2	4	_aComputational Intelligence.
650	2	4	_aComputer Communication Networks.
650	2	4	_aPattern Recognition.
650	2	4	_aArtificial Intelligence (incl. Robotics).
650	2	4	_aData Mining and Knowledge Discovery.
700	1		_aCelebi, M. Emre. _eeditor.
700	1		_aAydin, Kemal. _eeditor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783319242095
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-319-24211-8
912			_aZDB-2-ENG
942			_cEBK
999			_c53709 _d53709