Python data mining and machine learning in action

As demands for accountability by national and state authorities increase in breadth and depth, educators are caught in the squeeze if they do not have sufficient skills in data gathering and interpret

This book introduces soft computing methods that extend the envelope of problems that data mining can efficiently solve. It presents practical soft-computing approaches in data mining, including vari

Computer scientists mostly from South America, Europe, and Australia explain how to enhance the process of finding meaningful patterns in large bodies of data by defining prior knowledge about what th

O'Neil (Teachers College, Columbia U.), who is associated with a firm that specializes in action technologies, and Marsick (adult and organizational learning, Teachers College, Columbia U.) explain ho

The sixteen papers presented by Zhang (California State U.) and Tsai (U. of Illinois at Chicago) describe recent advances in machine learning applications in software engineering. They are organized i

Markov and Larose (computer science and statistics respectively, Central Connecticut State U.) seek ways to extract knowledge rather than merely come up with a pile of data by finding meaningful conne

Text mining is a new and exciting area of computer science research that tries to solve the crisis of information overload by combining techniques from data mining, machine learning, natural language processing, information retrieval, and knowledge management. Similarly, link detection – a rapidly evolving approach to the analysis of text that shares and builds upon many of the key elements of text mining – also provides new tools for people to better leverage their burgeoning textual data resources. The Text Mining Handbook presents a comprehensive discussion of the state-of-the-art in text mining and link detection. In addition to providing an in-depth examination of core text mining and link detection algorithms and operations, the book examines advanced pre-processing techniques, knowledge representation considerations, and visualization approaches. Finally, the book explores current real-world, mission-critical applications of text mining and link detection in such varied fields a

A practical, step-by-step approach to making sense out of data Making Sense of Data educates readers on the steps and issues that need to be considered in order to successfully complete a data analys

How Assessment Supports Learning: Learning-oriented Assessment in Action invites teachers in higher education to rethink the purposes of assessment and to revise their assessment practices in the inte

It is now possible to predict the future when it comes to crime. In Data Mining and Predictive Analysis, Dr. Colleen McCue describes not only the possibilities for data mining to assist law enforceme

Successfully competing in the new global economy requires immediate decision capability. This immediate decision capability requires quick analysis of both timely and relevant data. To support this an

Investigative Data Mining for Security and Criminal Detection is the first book to outline how data mining technologies can be used to combat crime in the 21st century. It introduces security manage

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 cu

In recent years machine learning has made its way from artificial intelligence into areas of administration, commerce, and industry. Data mining is perhaps the most widely known demonstration of this

A guide to machine learning approaches and their application to the analysis ofbiological data.

Provides an overview of data mining technology and how it is applied in a business environment. Material is not written in a technical style, but rather addresses the applied methodology behind implem