Quality Measures in Data Mining

Data mining analyzes large amounts of data to discover knowledge relevant to decision making. Typically, numerous pieces of knowledge are extracted by a data mining system and presented to a human user, who may be a decision-maker or a data-analyst. The user is confronted with the task of selecting the pieces of knowledge that are of the highest quality or interest according to his or her preferences. Since this selection is sometimes a daunting task, designing quality and interestingness measures has become an important challenge for data mining researchers in the last decade.

This volume presents the state of the art concerning quality and interestingness measures for data mining. The book summarizes recent developments and presents original research on this topic. The chapters include surveys, comparative studies of existing measures, proposals of new measures, simulations, and case studies. Both theoretical and applied chapters are included. Papers for this book were selected and reviewed for correctness and completeness by an international review committee.
Written for:

Researchers, engineers, graduate students in Computational Intelligence and Computer Science

Download link:


[Fast Download] Quality Measures in Data Mining

Related eBooks:
Building Applications with Spring 5 and Kotlin: Build scalable and reactive applications with Spring
Building Smart Drones with ESP8266 and Arduino
Take Control of Mojave
Take Control of iOS 12
Learn Raspberry Pi
Programming iOS 12: Dive Deep into Views, View Controllers, and Frameworks
Internet of Things with Raspberry Pi 3
Apple Training Series: Desktop and Portable Systems, 3rd Edition
My BlackBerry Curve
The Ultimate Raspberry Pi Handbook
iPad 2 All-in-One For Dummies, 3rd Edition
Scientists' and Engineers' guide yo DSP by S.Smith
Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.