Data Mining: A Heuristic Approach

Authors:
Hussein Abbass;Charles Newton;Ruhul Sarker
Affiliations:
-;-;-
Venue:
Data Mining: A Heuristic Approach
Year:
2002

Citing 0
Cited 7

Data mining with a simulated annealing based fuzzy classification system

Pattern Recognition
Data mining with a simulated annealing based fuzzy classification system

Pattern Recognition
Evolving model trees for mining data sets with continuous-valued classes

Expert Systems with Applications: An International Journal
A New Adaptive Neural Network Model for Financial Data Mining

ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Application of the active learning method to the retrieval of pigment from spectral remote sensing reflectance data

International Journal of Remote Sensing
Data mining with scatter search

EUROCAST'05 Proceedings of the 10th international conference on Computer Aided Systems Theory
Mining dichromatic colours from video

ICDM'06 Proceedings of the 6th Industrial Conference on Data Mining conference on Advances in Data Mining: applications in Medicine, Web Mining, Marketing, Image and Signal Mining

Quantified Score

Hi-index	0.00

Visualization

Abstract

From the Publisher:Real-life problems are known to be messy, dynamic and multi-objective, and involve high levels of uncertainty and constraints. Because traditional problem-solving methods are no longer capable of handling this level of complexity, heuristic search methods have attracted increasing attention in recent years for solving such problems. Inspired by nature, biology, statistical mechanics, physics and neuroscience, heuristic techniques are used to solve many problems where traditional methods have failed. Data Mining: A Heuristic Approach is a repository for the applications of these techniques in the area of data mining.