Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases -
-20% with code BOOKS
Shipping in 17-23 days
30-day return policy
Data Mining (DM) is the most commonly used name to describe such computational analysis of data and the results obtained must conform to several objectives such as accuracy, comprehensibility, interest for the user etc. Though there are many sophisticated techniques developed by various interdisciplinary fields only a few of them are well equipped to handle these multi-criteria issues of DM. Therefore, the ... Full description
You May Also Like
TOP
The Design of Everyday Things
-20% with code BOOKS
In stock at our supplier
TOP
If Anyone Builds It, Everyone Dies: The Case Against Superintelligent AI
Eliezer Yudkowsky, Nate Soares
-20% with code BOOKS
In stock at our supplier
TOP
We Are Not Machines: The Fight for the Future of Work
-20% with code BOOKS
In stock at our supplier
TOP
Open Circuits: The Inner Beauty of Electronic Components
Eric Schlaepfer, Windell Oskay
-20% with code BOOKS
In stock at our supplier
TOP
Get started with MicroPython on Raspberry Pi Pico: The Official Raspberry Pi Pico Guide
-20% with code BOOKS
In stock at our supplier
TOP
Practical Electronics for Inventors
-20% with code BOOKS
In stock at our supplier
TOP
Fundamentals of Aerodynamics ISE
Christopher Cadou, John D. Anderson
-20% with code BOOKS
In stock at our supplier
TOP
Nucleo Boards Programming with the STM32CubeIDE: Hands-on in more than 50 projects
-20% with code BOOKS
In stock at our supplier
TOP
Black Holes: The Key to Understanding the Universe
-20% with code BOOKS
In stock at our supplier
TOP
Professional SMD Assembly: Practical Low-Cost Methods for Reliable PCB Production
-20% with code BOOKS
In stock at our supplier
TOP
KiCad Like A Pro - Fundamentals and Projects: Getting started with the world's best open-source PCB tool
-20% with code BOOKS
In stock at our supplier
TOP
Make: Electronics: Learning by Discovery: A hands-on primer for the new electronics enthusiast
-20% with code BOOKS
In stock at our supplier
TOP
Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control
Steven L. Brunton, J. Nathan Kutz
-20% with code BOOKS
In stock at our supplier
TOP
Flowers For Algernon: A Modern Literary Classic
-20% with code BOOKS
In stock at our supplier
TOP
Foundations of Flavor: The Noma Guide to Fermentation: Including Step-By-Step Information on Making and Cooking with: Koji, Kombuchas, Shoyus, Misos, Vinegars, Garums, Lacto-Ferments and black Fruits Vegetables
-20% with code BOOKS
In stock at our supplier
TOP
Raspberry Pi 5 for Radio Amateurs: Program and Build Raspberry Pi 5 Based Ham Station Utilities with the RTL-SDR
-20% with code BOOKS
In stock at our supplier
TOP
Digital Design and Computer Architecture, RISC-V Edition
-20% with code BOOKS
In stock at our supplier
TOP
AI 2041: Ten Visions for Our Future
-20% with code BOOKS
In stock at our supplier
TOP
Mastering the Arduino Uno R4: Programming and Projects for the Minima and WiFi
-20% with code BOOKS
In stock at our supplier
Description
Data Mining (DM) is the most commonly used name to describe such computational analysis of data and the results obtained must conform to several objectives such as accuracy, comprehensibility, interest for the user etc. Though there are many sophisticated techniques developed by various interdisciplinary fields only a few of them are well equipped to handle these multi-criteria issues of DM. Therefore, the DM issues have attracted considerable attention of the well established multiobjective genetic algorithm community to optimize the objectives in the tasks of DM. The present volume provides a collection of seven articles containing new and high quality research results demonstrating the significance of Multi-objective Evolutionary Algorithms (MOEA) for data mining tasks in Knowledge Discovery from Databases (KDD). These articles are written by leading experts around the world. It is shown how the different MOEAs can be utilized, both in individual and integrated manner, in various ways to efficiently mine data from large databases.
More Information
| Publisher | Springer Berlin Heidelberg |
|---|---|
| Series | Studies in Computational Intelligence |
| Release year | 2008 |
| Cover type | Hardcover |
| EAN | 9783540774662 |