Mining the classification rules: the egyptian rice diseases as case study

Authors:
Mohammed E. El-Telbany
Affiliations:
Computer Engineering Department, Faculty of Engineering, Amman University, Jordan
Venue:
TELE-INFO'05 Proceedings of the 4th WSEAS International Conference on Telecommunications and Informatics
Year:
2005

Citing 2
Cited 1

C4.5: programs for machine learning

C4.5: programs for machine learning
Induction of Decision Trees

Machine Learning

Input space reduction for rule based classification

WSEAS Transactions on Information Science and Applications

Quantified Score

Hi-index	0.00

Visualization

Abstract

Applications of learning algorithms in knowledge discovery are promising and relevant area of research. It is offering new possibilities and benefits in real-world applications, helping us understand better mechanisms of our own methods of knowledge acquisition. Decision trees is one of learning algorithms which posses certain advantages that make it suitable for discovering the classification rule for data mining applications. This paper, intended to discover classification rules for the Egyptian rice diseases using the C4.5 decision trees algorithm. Experiments presenting a preliminary result to demonstrate the capability of C4.5 mine accurate classification rules suitable for diagnosis the disease.