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Advances in Machine Learning for Big Data Analysis

INTLLGNT SYS REF LIB: ADV MACH LRNG BIG DATA ANALYSIS

Information Technology

Computing & Information Technology

Gt Product Group

Binding Format

Marketing Imprint Name

B2B GT

CL Carton Count

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B2B & B2C

<P>This book focuses on research aspects of ensemble approaches of machine learning techniques that can be applied to address the big data problems. In this book, various advancements of machine learning algorithms to extract data-driven decisions from big data in diverse domains such as the banking sector, healthcare, social media, and video surveillance are presented in several chapters. Each of them has separate functionalities, which can be leveraged to solve a specific set of big data applications. This book is a potential resource for various advances in the field of machine learning and data science to solve big data problems with many objectives. It has been observed from the literature that several works have been focused on the advancement of machine learning in various fields like biomedical, stock prediction, sentiment analysis, etc. However, limited discussions have been carried out on application of advanced machine learning techniques in solving big data problems.</P>

Duration

Duration Unit Of Measure

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Front Cover.
Intelligent Systems Reference Library.
Other Frontmatter.
Title Page.
Copyright Page.
Preface.
Contents.
Editors and Contributors.
1: Multi-objective Ant Colony Optimization: An Updated Review of Approaches and Applications.
2: Cost-Effective Detection of Cyber Physical System Attacks.
3: A Prognostic Approach to Crime Analysis.
4: A Counter-Based Profiling Scheme for Improving Locality Through Data and Reducer Placement.
5: Hybridization of the Higher Order Neural Networks with the Evolutionary Optimization Algorithms&#x2014;An Application to Financial Time Series Forecasting.
6: Supply Chain Management (SCM): Employing Various Big Data and Metaheuristic Strategies.
7: Value of Random Vector Functional Link Neural Networks in Software Development Effort Estimation.
8: Hybrid Approach to Prevent Accidents at Railway: An Assimilation of Big Data, IoT and Cloud.
9: Hybrid Decision Tree for Machine Learning: A Big Data Perspective.

Advances in Machine Learning for Big Data Analysis.css-1p8rvzy{position:absolute;padding-left:8px;}

Advances in Machine Learning for Big Data Analysis