Elements of information theory
Elements of information theory
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Machine Learning
In Pursuit of Patterns in Data Reasoning from Data The Rough Set Way
TSCTC '02 Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing
Decision trees and flow graphs
RSCTC'06 Proceedings of the 5th international conference on Rough Sets and Current Trends in Computing
An efficient algorithm for inference in rough set flow graphs
Transactions on Rough Sets V
An extension of rough set approximation to flow graph based data analysis
RSCTC'10 Proceedings of the 7th international conference on Rough sets and current trends in computing
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Entropy is a fundamental principle in many disciplines such as information theory, thermodynamics, and more recently, artificial intelligence. In this article, a measure of entropy on Pawlak's mathematical flow graph is introduced. The predictability and quality of a flow graph can be derived directly from the entropy. An application to decision tree generation from a flow graph is examined. In particular, entropy measures on flow graphs lead to a new methodology of reasoning from data and shows rigorous relationships between flow graphs, entropy and decision trees.