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Data Mining And Mathematical Programming

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Data Mining And Mathematical Programming

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Author : Panos M. Pardalos
language : en
Publisher: American Mathematical Soc.
Release Date : 2008-04-09

Data Mining And Mathematical Programming written by Panos M. Pardalos and has been published by American Mathematical Soc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-09 with Computers categories.

Data mining aims at finding interesting, useful or profitable information in very large databases. The enormous increase in the size of available scientific and commercial databases (data avalanche) as well as the continuing and exponential growth in performance of present day computers make data mining a very active field. In many cases, the burgeoning volume of data sets has grown so large that it threatens to overwhelm rather than enlighten scientists. Therefore, traditional methods are revised and streamlined, complemented by many new methods to address challenging new problems. Mathematical Programming plays a key role in this endeavor. It helps us to formulate precise objectives (e.g., a clustering criterion or a measure of discrimination) as well as the constraints imposed on the solution (e.g., find a partition, a covering or a hierarchy in clustering). It also provides powerful mathematical tools to build highly performing exact or approximate algorithms. This book is based on lectures presented at the workshop on "Data Mining and Mathematical Programming" (October 10-13, 2006, Montreal) and will be a valuable scientific source of information to faculty, students, and researchers in optimization, data analysis and data mining, as well as people working in computer science, engineering and applied mathematics.

Data Mining And Mathematical Programming

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Author : Panos M. Pardalos
language : en
Publisher: American Mathematical Soc.
Release Date : 2008

Mathematics And Programming For Machine Learning With R

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Author : William B. Claster
language : en
Publisher:
Release Date : 2020

Mathematics And Programming For Machine Learning With R written by William B. Claster and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Machine learning categories.

Based on the author's experience teaching data science for more than 10 years, Mathematics and R Programming for Machine Learningreveals how machine learning algorithms do their magic and explains how logic can be implemented in code. It is designed to give students an understanding of the logic behind machine learning algorithms as well as how to program these algorithms. Written for novice programmers, the book goes step-by-step to develop coding skills needed to implement algorithms in R. The text begins with simple implementations and fundamental concepts of logic, sets, and probability before moving to coverage of powerful deep learning algorithms. The first eight chapters deal with probability-based machine learning algorithms, and the last eight chapters deal with artificial neural network-based machine learning. The first half of the text does not require mathematical sophistication, although familiarity with probability and statistics is helpful. The second half is written for students who have taken one semester of calculus. The book guides students, who are novice R programmers, through algorithms and their application to improve the ability to code and confidence in programming R and tackling advance R programming challenges. Highlights of the book include: More than 400 exercises A strong emphasis on improving programming skills and guiding beginners on implementing full-fledged algorithms. Coverage of fundamental computer and mathematical concepts including logic, sets, and probability In-depth explanations of the heart of AI and machine learning as well as the mechanisms that underly machine learning algorithms

Mathematical Analysis For Machine Learning And Data Mining

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Author : Dan A Simovici
language : en
Publisher: World Scientific
Release Date : 2018-05-22

Mathematical Analysis For Machine Learning And Data Mining written by Dan A Simovici and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-22 with Computers categories.

This compendium provides a self-contained introduction to mathematical analysis in the field of machine learning and data mining. The mathematical analysis component of the typical mathematical curriculum for computer science students omits these very important ideas and techniques which are indispensable for approaching specialized area of machine learning centered around optimization such as support vector machines, neural networks, various types of regression, feature selection, and clustering. The book is of special interest to researchers and graduate students who will benefit from these application areas discussed in the book. Related Link(s)

Mathematical Programming In Data Mining And Machine Learning

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Author : Katya Scheinberg
language : en
Publisher:
Release Date : 2008

Mathematical Programming In Data Mining And Machine Learning written by Katya Scheinberg and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.

Machine Learning And Data Mining Via Mathematical Programming Based Support Vector Machines

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Author : Glenn Fung
language : en
Publisher:
Release Date : 2003

Machine Learning And Data Mining Via Mathematical Programming Based Support Vector Machines written by Glenn Fung and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with categories.

Mathematical Methods For Knowledge Discovery And Data Mining

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Author : Giovanni Felici
language : en
Publisher: IGI Global Snippet
Release Date : 2008

Mathematical Methods For Knowledge Discovery And Data Mining written by Giovanni Felici and has been published by IGI Global Snippet this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Business & Economics categories.

Annotation The field of data mining has seen a demand in recent years for the development of ideas and results in an integrated structure. Mathematical Methods for Knowledge Discovery & Data Mining focuses on the mathematical models and methods that support most data mining applications and solution techniques, covering such topics as association rules; Bayesian methods; data visualization; kernel methods; neural networks; text, speech, and image recognition; and many others. This Premier Reference Source is an invaluable resource for scholars and practitioners in the fields of biomedicine, engineering, finance and insurance, manufacturing, marketing, performance measurement, and telecommunications.

Building And Solving Mathematical Programming Models In Engineering And Science

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Author : Enrique Castillo
language : en
Publisher: John Wiley & Sons
Release Date : 2011-10-24

Building And Solving Mathematical Programming Models In Engineering And Science written by Enrique Castillo and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10-24 with Mathematics categories.

Fundamental concepts of mathematical modeling Modeling is one of the most effective, commonly used tools in engineering and the applied sciences. In this book, the authors deal with mathematical programming models both linear and nonlinear and across a wide range of practical applications. Whereas other books concentrate on standard methods of analysis, the authors focus on the power of modeling methods for solving practical problems-clearly showing the connection between physical and mathematical realities-while also describing and exploring the main concepts and tools at work. This highly computational coverage includes: * Discussion and implementation of the GAMS programming system * Unique coverage of compatibility * Illustrative examples that showcase the connection between model and reality * Practical problems covering a wide range of scientific disciplines, as well as hundreds of examples and end-of-chapter exercises * Real-world applications to probability and statistics, electrical engineering, transportation systems, and more Building and Solving Mathematical Programming Models in Engineering and Science is practically suited for use as a professional reference for mathematicians, engineers, and applied or industrial scientists, while also tutorial and illustrative enough for advanced students in mathematics or engineering.

Principles Of Data Mining

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Author : Max Bramer
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-03-06

Principles Of Data Mining written by Max Bramer and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-03-06 with Computers categories.

This book explains the principal techniques of data mining: for classification, generation of association rules and clustering. It is written for readers without a strong background in mathematics or statistics and focuses on detailed examples and explanations of the algorithms given. This will benefit readers of all levels, from those who use data mining via commercial packages, right through to academic researchers. The book aims to help the general reader develop the necessary understanding to use commercial data mining packages, and to enable advanced readers to understand or contribute to future technical advances. Includes exercises and glossary.

Data Mining With R

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Author : Luís Torgo
language : en
Publisher: Chapman & Hall/CRC
Release Date : 2017

Data Mining With R written by Luís Torgo and has been published by Chapman & Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Business & Economics categories.

5.1 Problem Description and Objectives

Data Mining And Mathematical Programming

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