000 | 03891nam a22005895i 4500 | ||
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001 | 978-3-319-67588-6 | ||
003 | DE-He213 | ||
005 | 20220801215244.0 | ||
007 | cr nn 008mamaa | ||
008 | 171116s2018 sz | s |||| 0|eng d | ||
020 |
_a9783319675886 _9978-3-319-67588-6 |
||
024 | 7 |
_a10.1007/978-3-319-67588-6 _2doi |
|
050 | 4 | _aQ342 | |
072 | 7 |
_aUYQ _2bicssc |
|
072 | 7 |
_aTEC009000 _2bisacsh |
|
072 | 7 |
_aUYQ _2thema |
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_a006.3 _223 |
245 | 1 | 0 |
_aAdvances in Feature Selection for Data and Pattern Recognition _h[electronic resource] / _cedited by Urszula Stańczyk, Beata Zielosko, Lakhmi C. Jain. |
250 | _a1st ed. 2018. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2018. |
|
300 |
_aXVIII, 328 p. 37 illus., 20 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 |
||
490 | 1 |
_aIntelligent Systems Reference Library, _x1868-4408 ; _v138 |
|
505 | 0 | _aAn Introduction -- Attribute Selection Based on Reduction of Numerical Attribute During Discretization -- Improving Bagging Ensembles for Class Imbalanced Data by Active Learning -- Optimization of Decision Rules Relative to Length Based on Modified Dynamic Programming Approach -- Ranking-Based Rule Classifier Optimisation -- Attribute Selection in a Dispersed Decision-Making System -- Feature Selection Approach for Rule-based Knowledge Bases -- Feature Selection with a Genetic Algorithm for Classification of Brain Imaging Data. | |
520 | _aThis book presents recent developments and research trends in the field of feature selection for data and pattern recognition, highlighting a number of latest advances. The field of feature selection is evolving constantly, providing numerous new algorithms, new solutions, and new applications. Some of the advances presented focus on theoretical approaches, introducing novel propositions highlighting and discussing properties of objects, and analysing the intricacies of processes and bounds on computational complexity, while others are dedicated to the specific requirements of application domains or the particularities of tasks waiting to be solved or improved. Divided into four parts – nature and representation of data; ranking and exploration of features; image, shape, motion, and audio detection and recognition; decision support systems, it is of great interest to a large section of researchers including students, professors and practitioners. | ||
650 | 0 |
_aComputational intelligence. _97716 |
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650 | 0 |
_aArtificial intelligence. _93407 |
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650 | 0 |
_aPattern recognition systems. _93953 |
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650 | 0 |
_aData mining. _93907 |
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650 | 1 | 4 |
_aComputational Intelligence. _97716 |
650 | 2 | 4 |
_aArtificial Intelligence. _93407 |
650 | 2 | 4 |
_aAutomated Pattern Recognition. _931568 |
650 | 2 | 4 |
_aData Mining and Knowledge Discovery. _943271 |
700 | 1 |
_aStańczyk, Urszula. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _943272 |
|
700 | 1 |
_aZielosko, Beata. _eeditor. _0(orcid)0000-0003-3788-1094 _1https://orcid.org/0000-0003-3788-1094 _4edt _4http://id.loc.gov/vocabulary/relators/edt _943273 |
|
700 | 1 |
_aJain, Lakhmi C. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _943274 |
|
710 | 2 |
_aSpringerLink (Online service) _943275 |
|
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783319675879 |
776 | 0 | 8 |
_iPrinted edition: _z9783319675893 |
776 | 0 | 8 |
_iPrinted edition: _z9783319884523 |
830 | 0 |
_aIntelligent Systems Reference Library, _x1868-4408 ; _v138 _943276 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-319-67588-6 |
912 | _aZDB-2-ENG | ||
912 | _aZDB-2-SXE | ||
942 | _cEBK | ||
999 |
_c77286 _d77286 |