000 03379nam a2200577Ii 4500
001 9781315151274
003 FlBoTFG
005 20220711212818.0
006 m o d
007 cr
008 190122t20182019fluab ob 001 0 eng d
020 _a9781315151274(e-book : PDF)
035 _a(OCoLC)1079363767
040 _aFlBoTFG
_cFlBoTFG
_erda
050 4 _aQA76.9
_b.B45
072 7 _aBUS
_x061000
_2bisacsh
072 7 _aCOM
_x021030
_2bisacsh
072 7 _aCOM
_x037000
_2bisacsh
072 7 _aUN
_2bicscc
082 0 4 _a5.7
_223
100 1 _aMohanty, Soumya ,
_eauthor.
_919847
245 1 0 _aSwarm Intelligence Methods for Statistical Regression /
_cby Soumya Mohanty.
250 _aFirst edition.
264 1 _aBoca Raton, FL :
_bChapman and Hall/CRC,
_c[2018].
264 4 _c©2019.
300 _a1 online resource (136 pages) :
_b19 illustrations, text file, PDF
336 _atext
_2rdacontent
337 _acomputer
_2rdamedia
338 _aonline resource
_2rdacarrier
504 _aIncludes bibliographical references and index.
505 0 0 _tChapter 1 Introduction Chapter 2 Stochastic Optimization Theory Chapter 3 Evolutionary Computation and Swarm Intelligence Chapter 4 Particle Swarm Optimization Chapter 5 PSO Applications Appendix A Probability Theory Appendix B Splines Appendix C Analytical minimization.
520 3 _aA core task in statistical analysis, especially in the era of Big Data, is the fitting of flexible, high-dimensional, and non-linear models to noisy data in order to capture meaningful patterns. This can often result in challenging non-linear and non-convex global optimization problems. The large data volume that must be handled in Big Data applications further increases the difficulty of these problems. Swarm Intelligence Methods for Statistical Regression describes methods from the field of computational swarm intelligence (SI), and how they can be used to overcome the optimization bottleneck encountered in statistical analysis. Features Provides a short, self-contained overview of statistical data analysis and key results in stochastic optimization theory Focuses on methodology and results rather than formal proofs Reviews SI methods with a deeper focus on Particle Swarm Optimization (PSO) Uses concrete and realistic data analysis examples to guide the reader Includes practical tips and tricks for tuning PSO to extract good performance in real world data analysis challenges.
530 _aAlso available in print format.
650 7 _aCOMPUTERS / Database Management / Data Mining.
_2bisacsh
_912290
650 7 _aCOMPUTERS / Machine Theory.
_2bisacsh
_919848
650 7 _adata analysis.
_2bisacsh
_93163
650 7 _agenetic algorithms.
_2bisacsh
_93938
650 7 _ahigh-dimensional data.
_2bisacsh
_919849
650 7 _amulti-agent systems.
_2bisacsh
_919850
650 7 _aoptimization.
_2bisacsh
_919851
650 7 _aparametic regression.
_2bisacsh
_919852
650 0 _aBig data.
_94174
650 0 _aSwarm intelligence.
_96631
650 0 _aComputational intelligence.
_97716
650 0 _aRegression analysis.
_92504
655 0 _aElectronic books.
_93294
710 2 _aTaylor and Francis.
_910719
776 0 8 _iPrint version:
_z9781138558182
856 4 0 _uhttps://www.taylorfrancis.com/books/9781315151274
_zClick here to view
942 _cEBK
999 _c72206
_d72206