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020 _a9783030038953
024 7 _a10.1007/978-3-030-03895-3
_2doi
040 _bspa
_dES-MaUEC
_cES-MaUEC
050 4 _aQA248
_b2019 EB
100 1 _aNowicki, Robert K.
_eautor
_9671484
245 1 0 _aRough Set-Based Classification Systems
_cby Robert K. Nowicki.
264 1 _aCham
_bImprint: Springer
_c2019
300 _a1 recurso en línea (XIII, 188 páginas)
336 _2rdacontent
_aTexto
_btxt
337 _2rdamedia
_aelectrónico
_bc
338 _2rdacarrier
_arecurso electrónico
_bcr
347 _atext file
_bPDF
_2rda
490 0 _aStudies in Computational Intelligence
_x1860-949X
_v802
490 0 _aIntelligent Technologies and Robotics (Springer-42732)
505 0 _aIntroduction -- Rough Set Theory Fundamentals -- Rough Fuzzy Classification Systems -- Fuzzy Rough Classification Systems -- Rough Neural Network Classifier -- Rough Nearest Neighbour Classifier -- Ensembles of Rough Set-Based Classifiers -- Final Remarks.
520 3 _aThis book demonstrates an original concept for implementing the rough set theory in the construction of decision-making systems. It addresses three types of decisions, including those in which the information or input data is insufficient. Though decision-making and classification in cases with missing or inaccurate data is a common task, classical decision-making systems are not naturally adapted to it. One solution is to apply the rough set theory proposed by Prof. Pawlak. The proposed classifiers are applied and tested in two configurations: The first is an iterative mode in which a single classification system requests completion of the input data until an unequivocal decision (classification) is obtained. It allows us to start classification processes using very limited input data and supplementing it only as needed, which limits the cost of obtaining data. The second configuration is an ensemble mode in which several rough set-based classification systems achieve the unequivocal decision collectively, even though the systems cannot separately deliver such results.
988 _aPrimersemestre_2019_Robotics
650 7 _2embne
_aConjuntos, Teoría de
_9405124
776 0 8 _iPrinted edition:
_z9783030038946
776 0 8 _iPrinted edition:
_z9783030038960
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-03895-3
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
998 _aSI
_cm
_dz
_feng
_ggw
_h0
_b11/2019
_ek
_zSI