Cover Image

Swarm intelligence methods for statistical regression

A core task in Big Data analytics is the fitting of flexible, high-dimensional, models to noisy data in order to capture meaningful patterns. This book will describe methods from the field of computational swarm intelligence (SI) and how they can be used to solve optimization problems encountered in...

Full description

Saved in:

Bibliographic Details
Main Author:	Mohanty, Soumya D. (Author)
Format:	Book
Language:	English
Published:	Boca Raton, FL CRC Press, Taylor & Francis Group 2019
Subjects:	Big data. Swarm intelligence. Computational intelligence. Regression analysis.
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Swarm intelligence principles, advances, and applications
by: Hassanien, Aboul Ella, et al.
Published: (2016)

Swarm intelligence in data classification
by: Mohd. Afizi Mohd. Shukran, et al.

PARTICLE SWARM OPTIMIZATION (PSO) APPROACH FOR FEATURE SELECTION IN SENTIMENT ANALYSIS FOR PROPAGANDA ISSUE /
by: Muhammad Zakwan Muhamad Rodzi
Published: (2022)

Knowledge mining using intelligent agents
Published: (2011)

Modern regression methods
by: Ryan
Published: (1996)

Regression Analysis : AN INTUITIVE GUIDE FOR USING AND INTERPRETING LINEAR MODELS /
by: Frost, Jim
Published: (2019)

Artificial intelligence and big data the birth of a new intelligence
by: Iafrate, Fernando
Published: (2018)

The digital era big data stakes
Published: (2018)

Linear regression analysis
by: Seber, G. A. F., et al.
Published: (2003)

APPLIED REGRESSION ANALYSIS /
by: Draper, Norman Richard
Published: (1998)

Big data and computational intelligence in networking
Published: (2018)

Introduction to linear regression analysis
by: Montgomery, Douglas C., et al.
Published: (2020)

Regression analysis for categorical moderators
by: Aguinis, Herman
Published: (2004)

Handbook of research on design, control, and modeling of swarm robotics
Published: (2016)

Regression graphics ideas for studying regressions through graphics
by: Cook
Published: (1998)

Semiparametric regression for the social sciences
by: Keele 1974-
Published: (2008)

Data analytics the ultimate guide to big data analytics for business, data mining techniques, data collection, and business intelligence concepts
by: Jones, Herbert
Published: (2018)

Logistic regression from introductory to advanced concepts and applications
by: Menard, Scott
Published: (2010)

Fixed effects regression models
by: Allison, Paul David
Published: (2009)

A second course in statistics regression analyisis
by: Mendenhall, William, et al.
Published: (2020)

Security, privacy, and forensics issues in big data
Published: (2020)

Cognitive computing and big data analytics
by: Hurwitz, Judith, et al.
Published: (2015)

Design and analysis of experiments classical and regression approaches with SAS
by: Onyiah, Leonard C.
Published: (2009)

Mathematical methods for artificial intelligence and autonomous systems
by: Dougherty, Edward R.
Published: (1988)

Methods and applications of linear models regression and the analysis of variance
by: Hocking
Published: (1996)

Applied regression analysis for business and econimics
by: Dielman lhTerry E.

Bayesian regression modeling with INLA
by: Wang, Xiaofeng, et al.
Published: (2018)

System Analysis and Artificial Intelligence /
Published: (2023)

It’s All Analytics! : The Foundations of AI, Big Data, and Data Science Landscape for Professionals in Healthcare, Business, and Government /
by: Burk, Scott
Published: (2021)

Modern regression techniques using R a practical guide for students and researchers
by: Wright, Daniel B.
Published: (2009)

Modern regression techniques using R a practical guide for students and researchers
by: Wright, Daniel B.
Published: (2009)

Big data analytics tools and technology for effective planning
Published: (2018)

Spark big data cluster computing in production
by: Ganelin, Ilya, et al.
Published: (2016)

Research advances in the integration of big data and smart computing
Published: (2016)

Managing big data in cloud computing environments
Published: (2016)

Intelligence a very short introduction
by: Deary, Ian J.
Published: (2020)

Computational intelligence and its applications evolutionary computation, fuzzy logic, neural network and support vector machine techniques
Published: (2012)

The Kimball Group reader relentlessly practical tools for data warehousing and business intelligence
by: Kimball, Ralph, et al.
Published: (2016)

Computational intelligence a compendium
Published: (2008)

Artifical intelligence an engineering approach
by: Schalkoff