Research
Comparative Analysis of Random Forest and J48 Classifiers for “IRIS” Variety Prediction
Data mining may be a computerized technology that uses complicated algorithms to seek out relationships and trends in large databases, real or perceived, previously unknown to the retailer, to market decision support. Data mining is predicted to be one of the widespread recognition of the potential for analysis of past transaction data to enhance the standard of future business decisions. The aim is to arrange a set of knowledge items and classify them. In this paper, we apply two classifier algorithms: J48 (c4.5) and Random Forest on the IRIS dataset, and we compare their performance based on different measures.
Recognition of Tifinagh Characters using Self Organizing Map and Fuzzy k-Nearest Neighbor
In this paper we present a comparison between SOM (Self-Organization Map) neural network and Fuzzy Knearest Neighbor algorithms and their application to handwriting Tifinagh character recognition.The Box approach proposed in [1] is used for features extraction. Experimentation is carried out on a limited database of nearly 200 samples. The results showed that Fuzzy K-Nearest Neighbor had a very good performance.
