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Data Mining and Knowledge Discovery Handbook

Posted By: AvaxGenius
Data Mining and Knowledge Discovery Handbook

Data Mining and Knowledge Discovery Handbook by Oded Maimon
English | PDF | 2010 | 1269 Pages | ISBN : 0387098224 | 18.5 MB

Knowledge Discovery demonstrates intelligent computing at its best, and is the most desirable and interesting end-product of Information Technology. To be able to discover and to extract knowledge from data is a task that many researchers and practitioners are endeavoring to accomplish. There is a lot of hidden knowledge waiting to be discovered – this is the challenge created by today’s abundance of data.

The Art and Science of Machine Intelligence: With An Innovative Application for Alzheimer’s Detection from Speech

Posted By: AvaxGenius
The Art and Science of Machine Intelligence: With An Innovative Application for Alzheimer’s Detection from Speech

The Art and Science of Machine Intelligence: With An Innovative Application for Alzheimer’s Detection from Speech by Walker H. Land Jr.
English | EPUB | 2020 | 284 Pages | ISBN : 3030184951 | 27.17 MB

This volume presents several machine intelligence technologies, developed over recent decades, and illustrates how they can be combined in application. One application, the detection of dementia from patterns in speech, is used throughout to illustrate these combinations. This application is a classic stationary pattern detection task, so readers may easily see how these combinations can be applied to other similar tasks. The expositions of the methods are supported by the basic theory they rest upon, and their application is clearly illustrated. The book’s goal is to allow readers to select one or more of these methods to quickly apply to their own tasks.

Hybrid Random Fields: A Scalable Approach to Structure and Parameter Learning in Probabilistic Graphical Models

Posted By: AvaxGenius
Hybrid Random Fields: A Scalable Approach to Structure and Parameter Learning in Probabilistic Graphical Models

Hybrid Random Fields: A Scalable Approach to Structure and Parameter Learning in Probabilistic Graphical Models by Antonino Freno
English | PDF | 2011 | 217 Pages | ISBN : 3642203078 | 2.61 MB

This book presents an exciting new synthesis of directed and undirected, discrete and continuous graphical models. Combining elements of Bayesian networks and Markov random fields, the newly introduced hybrid random fields are an interesting approach to get the best of both these worlds, with an added promise of modularity and scalability. The authors have written an enjoyable book–-rigorous in the treatment of the mathematical background, but also enlivened by interesting and original historical and philosophical perspectives.