000			01542nam a2200349 a 4500
001			000542768
005			20240105150128.0
008			090109s2009 pauad rb 001 0 eng d
010			_a2008056149
020			_a9780898716757
020			_a0898716756
035			_a352922
040			_aDLC _bspa _cDLC _dUIASF
050		4	_aQA 76.9.D343 _bK356.2009
100	1		_aKamath, Chandrika
245	1	0	_aScientific data mining : _ba practical perspective / _cChandrika Kamath.
260			_aPhiladelphia : _bSociety for Industrial and Applied Mathematics, _c2009.
300			_axviii, 286 p. : _bil., gráficas ; _c25 cm.
504			_aIncluye referencias bibliográficas (325-277) e índice.
505	0		_aIntroduction -- Data mining in science and engineering -- Common themes in mining scientific data -- The scientific data mining process -- Reducing the size of the data -- Fusing different data modalities -- Enhancing image data -- Finding objects in the data -- Extracting features describing the objects -- Reducing the dimension of the data -- Finding patterns in the data -- Visualizing the data and validating the results -- Scientific data mining systems -- Lessons learned, challenges, and opportunities.
650		0	_aData mining
650		4	_aMinería de datos
650		0	_aScience _xDatabases
650		4	_aCiencia. _xBases de datos
650		0	_aEngineering _xDatabases
650		4	_aIngeniería. _xBases de datos
905			_a01
942		1	_cNEWBFXC1
999			_c511561 _d511561
980			_851 _gRonald RUIZ