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Contrast Data Mining

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Release : 2016-04-19
Genre : Business & Economics
Kind : eBook
Book Rating : 335/5 ( reviews)

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Book Synopsis Contrast Data Mining by : Guozhu Dong

Download or read book Contrast Data Mining written by Guozhu Dong. This book was released on 2016-04-19. Available in PDF, EPUB and Kindle. Book excerpt: A Fruitful Field for Researching Data Mining Methodology and for Solving Real-Life ProblemsContrast Data Mining: Concepts, Algorithms, and Applications collects recent results from this specialized area of data mining that have previously been scattered in the literature, making them more accessible to researchers and developers in data mining and

Data Mining Using Contrast-sets

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Release : 2011
Genre : Data mining
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Data Mining Using Contrast-sets by : Amit Satsangi

Download or read book Data Mining Using Contrast-sets written by Amit Satsangi. This book was released on 2011. Available in PDF, EPUB and Kindle. Book excerpt:

Exploiting the Power of Group Differences

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Release : 2022-05-31
Genre : Computers
Kind : eBook
Book Rating : 13X/5 ( reviews)

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Book Synopsis Exploiting the Power of Group Differences by : Guozhu Dong

Download or read book Exploiting the Power of Group Differences written by Guozhu Dong. This book was released on 2022-05-31. Available in PDF, EPUB and Kindle. Book excerpt: This book presents pattern-based problem-solving methods for a variety of machine learning and data analysis problems. The methods are all based on techniques that exploit the power of group differences. They make use of group differences represented using emerging patterns (aka contrast patterns), which are patterns that match significantly different numbers of instances in different data groups. A large number of applications outside of the computing discipline are also included. Emerging patterns (EPs) are useful in many ways. EPs can be used as features, as simple classifiers, as subpopulation signatures/characterizations, and as triggering conditions for alerts. EPs can be used in gene ranking for complex diseases since they capture multi-factor interactions. The length of EPs can be used to detect anomalies, outliers, and novelties. Emerging/contrast pattern based methods for clustering analysis and outlier detection do not need distance metrics, avoiding pitfalls of the latter in exploratory analysis of high dimensional data. EP-based classifiers can achieve good accuracy even when the training datasets are tiny, making them useful for exploratory compound selection in drug design. EPs can serve as opportunities in opportunity-focused boosting and are useful for constructing powerful conditional ensembles. EP-based methods often produce interpretable models and results. In general, EPs are useful for classification, clustering, outlier detection, gene ranking for complex diseases, prediction model analysis and improvement, and so on. EPs are useful for many tasks because they represent group differences, which have extraordinary power. Moreover, EPs represent multi-factor interactions, whose effective handling is of vital importance and is a major challenge in many disciplines. Based on the results presented in this book, one can clearly say that patterns are useful, especially when they are linked to issues of interest. We believe that many effective ways to exploit group differences' power still remain to be discovered. Hopefully this book will inspire readers to discover such new ways, besides showing them existing ways, to solve various challenging problems.

Principles of Data Mining

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Release : 2001-08-17
Genre : Computers
Kind : eBook
Book Rating : 907/5 ( reviews)

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Book Synopsis Principles of Data Mining by : David J. Hand

Download or read book Principles of Data Mining written by David J. Hand. This book was released on 2001-08-17. Available in PDF, EPUB and Kindle. Book excerpt: The first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics. 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.

Data Mining and Knowledge Discovery with Evolutionary Algorithms

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Release : 2013-11-11
Genre : Computers
Kind : eBook
Book Rating : 236/5 ( reviews)

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Book Synopsis Data Mining and Knowledge Discovery with Evolutionary Algorithms by : Alex A. Freitas

Download or read book Data Mining and Knowledge Discovery with Evolutionary Algorithms written by Alex A. Freitas. This book was released on 2013-11-11. Available in PDF, EPUB and Kindle. Book excerpt: This book integrates two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increasingly popular in the last few years, and their integration is currently an active research area. In general, data mining consists of extracting knowledge from data. The motivation for applying evolutionary algorithms to data mining is that evolutionary algorithms are robust search methods which perform a global search in the space of candidate solutions. This book emphasizes the importance of discovering comprehensible, interesting knowledge, which is potentially useful for intelligent decision making. The text explains both basic concepts and advanced topics

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