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020 _a9783030023577
024 7 _a10.1007/978-3-030-02357-7
_2doi
040 _bspa
_dES-MaUEC
_cES-MaUEC
050 4 _aQ325.5
_b2019 EB
245 0 0 _aMachine Learning Paradigms :
_bTheory and Application
_cedited by Aboul Ella Hassanien.
264 1 _aCham
_bImprint: Springer
_c2019
300 _a1 recurso en línea (IX, 474 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
_v801
490 0 _aIntelligent Technologies and Robotics (Springer-42732)
505 0 _aPart I: Machine Learning in Feature Selection -- Hybrid Feature Selection Method Based On The Genetic Algorithm And Pearson Correlation Coefficient -- Weighting Attributes and Decision Rules through Rankings and Discretisation Parameters -- Greedy Selection of Attributes to be Discretised -- Part II: Machine Learning in Classification and Ontology -- Machine learning for Enhancement Land Cover and Crop Types Classification.
520 3 _aThe book focuses on machine learning. Divided into three parts, the first part discusses the feature selection problem. The second part then describes the application of machine learning in the classification problem, while the third part presents an overview of real-world applications of swarm-based optimization algorithms. The concept of machine learning (ML) is not new in the field of computing. However, due to the ever-changing nature of requirements in today's world it has emerged in the form of completely new avatars. Now everyone is talking about ML-based solution strategies for a given problem set. The book includes research articles and expository papers on the theory and algorithms of machine learning and bio-inspiring optimization, as well as papers on numerical experiments and real-world applications.
988 _aPrimersemestre_2019_Robotics
650 7 _2embne
_aAprendizaje automático
_9166090
650 7 _2embne
_aInteligencia artificial
_9413115
700 1 _aHassanien, Aboul-Ella
_eeditor literario
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_997150
776 0 8 _iPrinted edition:
_z9783030023560
776 0 8 _iPrinted edition:
_z9783030023584
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-02357-7
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
998 _aSI
_cm
_dz
_feng
_ggw
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_b11/2019
_ek
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