Hierarchical Feature Selection For Knowledge Discovery

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Hierarchical Feature Selection For Knowledge Discovery

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Author : Cen Wan
language : en
Publisher: Springer
Release Date : 2018-11-29

Hierarchical Feature Selection For Knowledge Discovery written by Cen Wan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-29 with Computers categories.

This book is the first work that systematically describes the procedure of data mining and knowledge discovery on Bioinformatics databases by using the state-of-the-art hierarchical feature selection algorithms. The novelties of this book are three-fold. To begin with, this book discusses the hierarchical feature selection in depth, which is generally a novel research area in Data Mining/Machine Learning. Seven different state-of-the-art hierarchical feature selection algorithms are discussed and evaluated by working with four types of interpretable classification algorithms (i.e. three types of Bayesian network classification algorithms and the k-nearest neighbours classification algorithm). Moreover, this book discusses the application of those hierarchical feature selection algorithms on the well-known Gene Ontology database, where the entries (terms) are hierarchically structured. Gene Ontology database that unifies the representations of gene and gene products annotation provides the resource for mining valuable knowledge about certain biological research topics, such as the Biology of Ageing. Furthermore, this book discusses the mined biological patterns by the hierarchical feature selection algorithms relevant to the ageing-associated genes. Those patterns reveal the potential ageing-associated factors that inspire future research directions for the Biology of Ageing research.

Principles Of Data Mining And Knowledge Discovery

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Author :
language : en
Publisher:
Release Date : 2001

Principles Of Data Mining And Knowledge Discovery written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Data mining categories.

Data Warehousing And Knowledge Discovery

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Author :
language : en
Publisher:
Release Date : 2004

Data Warehousing And Knowledge Discovery written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Data mining categories.

Advances In Intelligent Data Analysis

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Author :
language : en
Publisher:
Release Date : 2003

Advances In Intelligent Data Analysis written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Expert systems (Computer science) categories.

Feature Selection For Knowledge Discovery And Data Mining

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Author : Huan Liu
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Feature Selection For Knowledge Discovery And Data Mining written by Huan Liu 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 2012-12-06 with Computers categories.

As computer power grows and data collection technologies advance, a plethora of data is generated in almost every field where computers are used. The com puter generated data should be analyzed by computers; without the aid of computing technologies, it is certain that huge amounts of data collected will not ever be examined, let alone be used to our advantages. Even with today's advanced computer technologies (e. g. , machine learning and data mining sys tems), discovering knowledge from data can still be fiendishly hard due to the characteristics of the computer generated data. Taking its simplest form, raw data are represented in feature-values. The size of a dataset can be measUJ·ed in two dimensions, number of features (N) and number of instances (P). Both Nand P can be enormously large. This enormity may cause serious problems to many data mining systems. Feature selection is one of the long existing methods that deal with these problems. Its objective is to select a minimal subset of features according to some reasonable criteria so that the original task can be achieved equally well, if not better. By choosing a minimal subset offeatures, irrelevant and redundant features are removed according to the criterion. When N is reduced, the data space shrinks and in a sense, the data set is now a better representative of the whole data population. If necessary, the reduction of N can also give rise to the reduction of P by eliminating duplicates.

Data Mining And Knowledge Discovery

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Author :
language : en
Publisher:
Release Date : 2003

Data Mining And Knowledge Discovery written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Data mining 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.

Advances In Distributed And Parallel Knowledge Discovery

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Author : Hillol Kargupta
language : en
Publisher: AAAI Press
Release Date : 2000

Advances In Distributed And Parallel Knowledge Discovery written by Hillol Kargupta and has been published by AAAI Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Computers categories.

This book presents introductions to DKD and PKD, extensive reviews of the field, and state-of-the-art techniques. Foreword by Vipin Kumar Knowledge discovery and data mining (KDD) deals with the problem of extracting interesting associations, classifiers, clusters, and other patterns from data. The emergence of network-based distributed computing environments has introduced an important new dimension to this problem--distributed sources of data. Traditional centralized KDD typically requires central aggregation of distributed data, which may not always be feasible because of limited network bandwidth, security concerns, scalability problems, and other practical issues. Distributed knowledge discovery (DKD) works with the merger of communication and computation by analyzing data in a distributed fashion. This technology is particularly useful for large heterogeneous distributed environments such as the Internet, intranets, mobile computing environments, and sensor-networks.When the data sets are large, scaling up the speed of the KDD process is crucial. Parallel knowledge discovery (PKD) techniques addresses this problem by using high-performance multiprocessor machines. This book presents introductions to DKD and PKD, extensive reviews of the field, and state-of-the-art techniques. Contributors Rakesh Agrawal, Khaled AlSabti, Stuart Bailey, Philip Chan, David Cheung, Vincent Cho, Joydeep Ghosh, Robert Grossman, Yi-ke Guo, John Hale, John Hall, Daryl Hershberger, Ching-Tien Ho, Erik Johnson, Chris Jones, Chandrika Kamath, Hillol Kargupta, Charles Lo, Balinder Malhi, Ron Musick, Vincent Ng, Byung-Hoon Park, Srinivasan Parthasarathy, Andreas Prodromidis, Foster Provost, Jian Pun, Ashok Ramu, Sanjay Ranka, Mahesh Sreenivas, Salvatore Stolfo, Ramesh Subramonian, Janjao Sutiwaraphun, Kagan Tummer, Andrei Turinsky, Beat Wüthrich, Mohammed Zaki, Joshua Zhang

Proceedings Of The International Ieee Conference On Tools For Artificial Intelligence

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Author :
language : en
Publisher:
Release Date : 2003

Proceedings Of The International Ieee Conference On Tools For Artificial Intelligence written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Algorithms categories.

Ijcnn 99

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Author : IEEE Neural Networks Council
language : en
Publisher: Institute of Electrical & Electronics Engineers(IEEE)
Release Date : 1999

Ijcnn 99 written by IEEE Neural Networks Council and has been published by Institute of Electrical & Electronics Engineers(IEEE) this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Computers categories.

IJCNN '99 spans the neural network field from neurons to consciousness, training algorithms to robotics, chaos to control, fuzzy logic to evolutionary computing. Starting with a symposium on biological neural networks, it explores the potential impact of neurobiological discoveries.