Principles of Data Mining (Adaptive Computation and Machine Learning)

Book Description

The growing interest in data mining is motivated by a common problem across disciplines: how does one store, access, model, and ultimately describe and understand very large data sets? Historically, different aspects of data mining have been addressed independently by different disciplines. This is the first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics.

The book consists of three sections. The first, foundations, provides a tutorial overview of the principles underlying data mining algorithms and their application. The presentation emphasizes intuition rather than rigor. The second section, data mining algorithms, shows how algorithms are constructed to solve specific problems in a principled manner. The algorithms covered include trees and rules for classification and regression, association rules, belief networks, classical statistical models, nonlinear models such as neural networks, and local "memory-based" models. The third section shows how all of the preceding analysis fits together when applied to real-world data mining problems. Topics include the role of metadata, how to handle missing data, and data preprocessing.

Customer Reviews:

make sure you are right audience.......2005-12-02

It's not that this is a bad book, but you have to make sure you are right audience. The book offers very high-level overviews on various techniques of data mining, but it is almost impossible to learn how to really implement them. Since there are no exercises after each chapter you probably already know who the target audience of the book are.

It shows me many examples.......2005-04-08

Even if it is bad as all the gentlemen said, I think at least it gives me many examples which are not mentioned in other books before.

Very, Very, Very Bad Book !.......2004-12-23

I am a professional in the field of data mining (over 10 years experience). I am always taking classes and reading on the subject. This book was a required text in a grad class I was taking in the evenings. I was excited because I had heard so many good things about it.

The book is indescribably bad.

It is bad if you want theory.
It is bad if you want practical advice.
It is just plain bad.

BAD! BAD! BAD!

Do yourself a favor and go out and get the books by Gordon Linoff et. al. (Mastering Data Mining and Data Mining Techniques). I believe that Amazon will sell you both for not much more money than if you buy this book. Either one of those books is better than this! (I recommend buying both, you won't be sorry!)

SAVE YOUR MONEY, AVOID THIS BOOK !!!

Good book for overall breadth of alogrithms.........2004-08-15

Very good book for a general overview of data mining algorithms. Covers a wide variety of DM approaches.. however lacks concrete examples to clear concepts thoroughly. I especially liked Chapter-5 which gives a general framework to look at any DM algorithm. This clears confusion created by so many diverse algorithms with overlapping concepts and applications.

Great book with a great layout!.......2004-03-15

I'd been struggling with the seemingly infinite ways to approach data mining and this book cleared it all up for me. It is absolutely full of information and is a great base reference. It does not contain complete algorithms or step by step instructions (you can get those anywhere these days) but instead is a comprehensive survey of all the best known methods for data mining. I really like how the authors combined classical mining techniques with more modern ones (ex: Bayesian Networks). Other books try to stay in one camp or the other, all while denying that they use very similar sub-components.

Book Description

The field of computer vision combines techniques from physics, mathematics, psychology, artificial intelligence, and computer science to examine how machines might construct meaningful descriptions of their surrounding environment. The editors of this volume, prominent researchers and leaders of the SRI International AI Center Perception Group, have selected sixty papers, most published since 1980, with the viewpoint that computer vision is concerned with solving seven basic problems:

Reconstructing 3D scenes from 2D images
Decomposing images into their component parts
Recognizing and assigning labels to scene objects
Deducing and describing relations among scene objects
Determining the nature of computer architectures that can support the visual function
Representing abstractions in the world of computer memory
Matching stored descriptions to image representation

Each chapter of this volume addresses one of these problems through an introductory discussion, which identifies major ideas and summarizes approaches, and through reprints of key research papers. Two appendices on crucial assumptions in image interpretation and on parallel architectures for vision applications, a glossary of technical terms, and a comprehensive bibliography and index complete the volume.

Expert Systems: Principles and Programming, Third Edition: Principles and Programming

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Up-to-date, accessible and concise. Great introduction to expert systems
Expert Systems: Principles and Programming, Fourth Edition
Worth every penny
Great book! Gives an overview of CLIPS main features.
Basic instruction on AI programming

Expert Systems: Principles and Programming, Third Edition: Principles and Programming
Joseph C. Giarratano , and Gary D. Riley
Manufacturer: Course Technology
ProductGroup: Book
Binding: Hardcover

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ASIN: 0534950531

Book Description

This book combines coverage of expert systems theory with coverage of practical applications using CLIPS, an expert systems shell widely used in government, industry, and education. The result is a self-contained book and CD-ROM package for computer science, engineering, and CIS/MIS students and professionals that provides the conceptual background and programming tools needed to understand and implement expert systems.

Customer Reviews:

Up-to-date, accessible and concise. Great introduction to expert systems.......2007-04-20

The 4th edition has remarkable changes compared to the 3rd edition, which was written in 1990. Almost all the references are highly up-to-date, new trends in the AI field and new applications leveraging expert systems are introduced all through this book. The content ranges from an overview to the technology of Expert Systems, the basic scientific foundation of Expert Systems and the CLIPS tool for implementing expert systems. There are two chapters about reasoning under uncertainty and inexact reasoning, which are the ways the AI systems are heading. Things like semantic web, its advantage and problems are very well sorted out in the first chapter. The authors put a good deal of humour into the text all through this book, the formal logic stuff is not that boring as it usually appears in other book. I wish I had had this book as my first book for formal logic/deduction systems. The mathematical mechanisms for things like resolution/deduction are explained with plenty of well-arranged diagrams and tables to help readers understand better. Every chapter comes with well-designed assignments. An excellent text book for introductory AI courses (I believe a motivated high-school kid will have no problem to understand the book since it is so well written). And also a good reference for those who need to look up basic concepts while engineering expert systems. I'm constructing an expert system at the moment, got this book 2 weeks ago and it's already dog-eared on my desk. For its targeted audience, this book is truly the best-of-breed. Highly recommended.

Expert Systems: Principles and Programming, Fourth Edition .......2006-02-23

An excellent text for a first course in Expert systems.

Worth every penny.......2003-08-13

This book gives a reasonable, detailed and seriuous account on expert system. A detailed presentation of the CLIPS expert-system language, along with the interpreter, is provided.

Excellent for starting work on expert systems as part of integrated software packages.

Great book! Gives an overview of CLIPS main features........1999-04-06

The authors give a good cursory background on knowledge representation within AI. Chapters 7 - 12, present CLIPS syntax and usage. The information in these chapters helped me to develop a simulation involving four intelligent agents, colloborating via a blackboard. The book provides no details with respect to CLIPS object-oriented capabilities (COOL), but this is something that can be learned through CLIP's accompanying documentation. I highly recommend this book to anyone wanting to know more about expert systems or CLIPS.

Basic instruction on AI programming.......1997-11-11

Provided good basic understanding of AI with example program, CLIPS, enclosed( floppy disk), well written with understandable examples

Principles of Data Mining (Undergraduate Topics in Computer Science)

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Principles of Data Mining (Undergraduate Topics in Computer Science)
Max Bramer
Manufacturer: Springer
ProductGroup: Book
Binding: Paperback

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ASIN: 1846287650

Book Description

Data Mining, the automatic extraction of implicit and potentially useful information from data, is increasingly used in commercial, scientific and other application areas.

This book explains and explores 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 should prove of value to readers of all kinds, from those whose only use of data mining techniques will be via commercial packages right through to academic researchers.

This book aims to help the general reader develop the necessary understanding to use commercial data mining packages discriminatingly, as well as enabling the advanced reader to understand or contribute to future technical advances in the field. Each chapter has practical exercises to enable readers to check their progress. A full glossary of technical terms used is included.

Design Principles for the Immune System and Other Distributed Autonomous Systems (Santa Fe Institute Studies in the Sciences of Complexity Proceedings)

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Agent-based modeling in medicine

Design Principles for the Immune System and Other Distributed Autonomous Systems (Santa Fe Institute Studies in the Sciences of Complexity Proceedings)
Lee A. Segel
Manufacturer: Oxford University Press
ProductGroup: Book
Binding: Hardcover

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ASIN: 0195136993

Book Description

Design Principles for the Immune System and Other Distributed Autonomous Systems is the first book to examine the inner workings of such a variety of distributed autonomous systems--from insect colonies to high level computer programs to the immune system. It offers insight into the fascinating world of these systems that emerge from the interactions of seemingly autonomous components and brings us up-to-date on the state of research in these areas. Using the immune system and certain aspects of its functions as a primary model, this book examines many of the most interesting and troubling questions posed by complex systems. How do systems choose the right set of agents to perform appropriate actions with appropriate intensities at appropriate times? How in the immune system, ant colonies and metabolic networks does the diffusion and binding of a large variety of chemicals to their receptors permit coordination of system action? What advantages drive the various systems to complexity, and by what mechanisms do the systems cope with the tendency toward unwieldiness and randomness of large complex systems?

Customer Reviews:

Agent-based modeling in medicine.......2003-01-23

Design Principles was written by a collection of authors specializing in diverse fields from computer scientists, theoretical biologist, pathologist, chemists and neurologists. The book began as a workshop held at the Sante Fe Institute in 1999 by the same name. While it is not a collection of abstracts and papers from this workshop, it did serve as the motivating factor to write the book. Design Principles starts with a description of the immune system that serves as a basic introduction both to the topic and to the biases of the multiple authors. Steven Hofmeyr offers a "gentle introduction to the immune system for researchers who do not have much background in immunology." (p.3) The chapter is titled "Introduction to the Immune System". Right off the biases of the book are exposed as Hofmeyr has a Ph.D. in computer sciences with a focus on information detection and distribution. Hofmeyr does an excellent job describing very complex biology without assuming that the reader has a background in either immunology or systems. While the author is gentle in his presentation the chapter is very dense with information which one hopes will be reiterated as one needs the information further in the book. Overall, I would recommend this book to anyone who is interested in pursuing agent based modeling of biological systems. This book would be particularly interesting to those pursing interests in modeling the process of immunity. My final criticism would be that the title is a bit misleading as I would suggest that the book only gives limited mention and thought to other types of autonomous systems with the exception of Bonabeau's description of control mechanisms learned from social insects and Gordon's chapter titled, "Task Allocation in Ant Colonies."

Principles Of Data Mining And Knowledge Discovery (Lecture Notes in Computer Science)

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Principles Of Data Mining And Knowledge Discovery (Lecture Notes in Computer Science)
Jan M., Ed. Zytkow
Manufacturer: Springer
ProductGroup: Book
Binding: Paperback

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ASIN: 3540664904

Book Description

This book constitutes the refereed proceedings of the Third European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD'99, held in Prague, Czech Republic in September 1999.
The 28 revised full papers and 48 poster presentations were carefully reviewed and selected from 106 full papers submitted. The papers are organized in topical sections on time series, applications, taxonomies and partitions, logic methods, distributed and multirelational databases, text mining and feature selection, rules and induction, and interesting and unusual issues.

Principles Of Visual Information Retrieval (ADVANCES IN PATTERN RECOGNITION)

Average customer rating:

Great for researchers
Dry and Fragmented
Book content obselete
Excellent Review of State of the Art

Principles Of Visual Information Retrieval (ADVANCES IN PATTERN RECOGNITION)
M. S. Lew
Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover

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ASIN: 1852333812

Book Description

Principles of Visual Information Retrieval introduces the basic concepts and techniques in VIR and develops a foundation that can be used for further research and study.
Divided into 2 parts, the first part describes the fundamental principles. A chapter is devoted to each of the main features of VIR, such as colour, texture and shape-based search. There is coverage of search techniques for time-based image sequences or videos, and an overview of how to combine all the basic features described and integrate context into the search process.
The second part looks at advanced topics such as multimedia query, specification, visual learning and semantics, and offers state-of-the-art coverage that is not available in any other book on the market.
This book will be essential reading for researchers in VIR, and for final year undergraduate and postgraduate students on courses such as Multimedia Information Retrieval, Multimedia Databases, Computer Vision and Pattern Recognition.

Customer Reviews:

Great for researchers.......2005-12-02

As a researcher in multimedia search (at Google), I absolutely love this book! It abounds with tremendously useful information to computer vision and multimedia search developers such as the brilliant chapters on color, texture, shape, and similarity measures. These go far beyond any other books on the market now even though they were written in 2000. I read on the Amazon site some criticisms of this book but I suspect they were written by undergraduates - i.e. No PhD would criticize a work published in early 2001 for only having references from 2000.

My only criticism of this book is that the reader should have expertise in fundamentals of image processing or computer vision beforehand, know what a color space, texture, etc. Read the CV book by Ponce and Forsyth first.

Dry and Fragmented.......2005-05-02

This book was quite a disappointment. The equations the author throws at the reader are extremely abstract and do not get elaborated. I don't think you will be able to implement any of these algorithms in a language like C++ because many details are missing. Most explanations are not self-contained; they usually go along the lines of "[author] uses this function to do blah blah..."

Book content obselete.......2003-06-17

It is indeed true that this is perhaps one of very few books on this important subject. Unfortunately, the content of the book is mainly obselete. It does not contain the start-of-art work since 2000. I am quite disappointed.

Excellent Review of State of the Art.......2002-07-19

There are only two books which cover the new area
of visual information retrieval. One is by Alberto del Bimbo
and gives a good introduction to the subject. It is
written well, but leaves the reader wondering what the
state of the art is.

This book by Prof. Lew covers the state of the art in the
fundamentals of color, texture, shape, and video. Prof. Lew's
book has each fundamental area written by the leading
expert so the material is fresh and truly state of the art.
These experts include the leading researchers from MIT,
Boston University, Univ. of Illinois, etc.

This is the only choice for an advanced book on visual
information retrieval - one for graduate students or
leading edge developers.

Book Description

Neuromorphic engineers work to improve the performance of artificial systems through the development of chips and systems that process information collectively using primarily analog circuits. This book presents the central concepts required for the creative and successful design of analog VLSI circuits. The discussion is weighted toward novel circuits that emulate natural signal processing. Unlike most circuits in commercial or industrial applications, these circuits operate mainly in the subthreshold or weak inversion region. Moreover, their functionality is not limited to linear operations, but also encompasses many interesting nonlinear operations similar to those occurring in natural systems. Topics include device physics, linear and nonlinear circuit forms, translinear circuits, photodetectors, floating-gate devices, noise analysis, and process technology.

Genetic Algorithms - Principles and Perspectives: A Guide to GA Theory (Operations Research/Computer Science Interfaces Series)

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A must-read for anyone with an interest in GA theory

Genetic Algorithms - Principles and Perspectives: A Guide to GA Theory (Operations Research/Computer Science Interfaces Series)
Colin R. Reeves , and Jonathan E. Rowe
Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover

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ASIN: 1402072406

Book Description

Genetic Algorithms (GAs) have become a highly effective tool for solving hard optimization problems. As their popularity has increased, the number of GA applications has grown in more than equal measure. Genetic Algorithm theory, however, has not kept pace with the growing use and application of GAs. Most book-length treatments of GAs provide only a cursory discussion of theory and this discussion primarily focuses on the traditional view, which depends heavily on the concept of a "schema".
Genetic Algorithms: Principles and Perspectives: A Guide to GA Theory is a survey of some important theoretical contributions, many of which have been proposed and developed in the Foundations of Genetic Algorithms series of workshops. However, this theoretical work is still rather fragmented, and the authors believe that it is the right time to provide the field with a systematic presentation of the current state of theory in the form of a set of theoretical perspectives. The authors do this in the interest of providing students and researchers with a balanced foundational survey of some recent research on GAs. The scope of the book includes chapter-length discussions of Basic Principles, Schema Theory, "No Free Lunch", GAs and Markov Processes, Dynamical Systems Model, Statistical Mechanics Approximations, Predicting GA Performance, Landscapes and Test Problems.
The authors have worked hard to make the book as accessible as possible for students and researchers. An undergraduate-level mathematical understanding of linear algebra and stochastic processes is assumed. For those readers who have not encountered GAs before, a comprehensive survey of GA concepts is provided and the variety of ways in which GAs can be implemented is outlined. Exercises are provided at the ends of the chapters with the express purpose of aiding understanding of the concepts discussed and to whet the reader's appetite for pursuing theoretical research in GAs.

Customer Reviews:

A must-read for anyone with an interest in GA theory.......2007-10-07

Reeves and Rowe provide a very readable overview of what is currently known about evolutionary algorithms. While the book provides very good coverage of several recent models of GA dynamics, it would be worth the money if only for the chapter on the dynamical systems treatment of GAs.

Vose's "The Simple Genetic Algorithm" is a brilliant piece of work, but it also holds the distinction of being the earliest in a book that I have ever become utterly, completely, hopelessly lost. I refer to this book as "the one I use to figure out what Vose was talking about."

Beautiful Mates: Applying Principles of Beauty to Computer Chess Heuristics

Average customer rating:

Good, but could be better.
I like it!
Original and Interesting - when is there a follow up??
Disappointing
Very unimportant research.

Beautiful Mates: Applying Principles of Beauty to Computer Chess Heuristics
Ben P. Walls
Manufacturer: Dissertation.com
ProductGroup: Book
Binding: Paperback

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ASIN: 1581120095

Download Description

A synopsis of eminent computer chess programs reveal that they are designed around a 'brute force' approach. An argument is made that by continuing the 'brute force' search approach, computer chess development is moving away from human evaluation methods. Research is done into studies of evaluation methods, and a discovery is made that humans use a form of intuition, called their 'sense of beauty', to choose the best chess move. A paper by Margulies is cited which formulates principles of beauty which apply to chess. Three versions of a chess program are developed, using no heuristics, standard chess heuristics, and beauty heuristics formulated from Margulies principles. The performance of the three versions of the program are compared using chess puzzles, and rated for how quickly they find the solution, and how few nodes they evaluate. Graphs are produced from the results of these tests, showing that beauty heuristics are, on average, 15% faster at finding the solution, and evaluate 10% fewer nodes. An improvement is implemented in all versions of the program which biases the search towards better moves, resulting in the beauty heuristics success rising to an average of 25% faster to the solution, and evaluating 33% fewer nodes, than the other heuristics. It is concluded that the beauty heuristics are closer to the way that humans evaluate chess positions.

Customer Reviews:

Good, but could be better........2002-07-19

An interesting read, but don't agree that Beauty is the factor that makes a chess player better. The eight concepts quoted from Margulies do not always help the computer play chess in a more human way. I think the human chess player has more principles used. For example, setting traps, pins and using combos. The human is more creative and doesn't use Beauty as described in the book to determine his/her actions. It is a far cry from playing like Fischer. This just shows how much more we have yet to explore in human learning and cognition.

I like it!.......2000-12-06

Good book, interesting topic. A little weird, but some original ideas, including a good section on alternative search.

Original and Interesting - when is there a follow up??.......1999-09-16

This is an orginal book, following an interesting proposal to get Computer chess games to 'think' more like human players. It is clear the author values this approach more than current 'brute force' search, and I must admit, I am swayed by his arguments (e.g. that the Deep Blue v Kasparov match did nothing to advance computer chess) - although I could have done with more results to convince me. I think the reader from Concord, MA missed the point of the book - the author never says he is proposing a 'better' (i.e. higher ELO) chess program - just one that thinks and plays more like a human (from an AI research perspective). To conclude, if you are looking for a book about conventional (outdated?) computer chess programming then this is of little interest. However, if you are after a novel book on the quest to 'capture' what goes on in the human mind when analysing problems, and how to represent that in, for example, chess problems, then this book is a good starting point.

Disappointing.......1999-07-18

This is a book bound version of a simple article comparing simple chess heuristics and simple + "beauty" heuristics as an attempt to emulate human chess thinking, where the "beauty" heuristics follow now outdated ideas in human 'intuition". The resulting programs are subjected to relatively simple mate in 2, 3 and the odd mate in 4 and 5 chess problems. The resulting time and nodes analysed between the two systems are probably statistically insignificant as only 24 problems are studied. An interesting read, but by no means revolutionary.

Very unimportant research........1999-07-08

This dissertation investigations problems of the mate-in-two variety, and shows that a few heuristics that correspond to the human concept of "beauty" tend to reduce solution times (10% to 33%). My disappointment arises because this is not a difficult problem; there isn't a chess program on the marketplace that can't solve mate-in-N problems in the blink of an eye. Furthermore, the advantage obtained through these heuristics is very minor; on a small sample of positions it is always possible to tune one's chess engine to obtain comparable speed-ups. My conclusion is that the author's time at the University of Sussex was not well spent.

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