Corresponding Author: Hamedoun Lamiae Laboratory LIROSA, Department of Computer Science, Faculty of Sciences, Abdelmalek Essaadi University, Mhannech II, BP: 2121, Tetouan, Morocco Tel: +212 662 12 32 33 Email: [email protected] Abstract: The present paper proposes a new Hybrid clustering Process based on Fuzzy Genetic System. The proposed Approach consists of two steps: (1) Using a method ...

The key point in design of radial basis function networks is to specify the number and the locations of the centers. Several heuristic hybrid learning methods, which apply a clustering algorithm for locating the centers and subsequently a linear leastsquares method for the linear weights, have been previously suggested. These hybrid methods can be put into two groups, which will be called as in...

This paper shows that decision trees can be used to improve the performance of case-based learning (CBL) systems. We introduce a performance task for machine learning systems called semi-exible prediction that lies between the classiication task performed by decision tree algorithms and the exible prediction task performed by conceptual clustering systems. In semi-exible prediction, learning sh...

In this paper a class of hybrid-fuzzy models is presented, where binary membership functions are used to capture the hybrid behavior. We describe a hybrid-fuzzy identification methodology for nonlinear hybrid systems with mixed continuous and discrete states that uses fuzzy clustering and principal component analysis. The method first determines the hybrid characteristic of the system inspired ...

In this paper, we use two-stage hybrid models consisting of unsupervised clustering techniques and decision trees with boosting on two different data sets and evaluate the models in terms of top decile lift. We examine two different approaches for hybridization of the models for utilizing the results of clustering based on various attributes related to service usage and revenue contribution of ...

A hybrid approach for intrusion detection in computer networks is presented in this paper. The proposed approach combines an evolutionary-based fuzzy system with an Ant Colony Optimization procedure to generate high-quality fuzzy-classification rules. We applied our hybrid learning approach to network security and validated it using the DARPA KDD-Cup99 benchmark data set. The results indicate t...

Recently, ranking-based clustering on heterogeneous information network has emerged, which shows its advantages on the mutual promotion of clustering and ranking. However, these algorithms are restricted to information network only containing heterogeneous relations. In many applications, networked data are more complex and they can be represented as a hybrid network which simultaneously includ...

Background and Objectives: Stock price prediction has become one of the interesting and also challenging topics for researchers in the past few years. Due to the non-linear nature of the time-series data of the stock prices, mathematical modeling approaches usually fail to yield acceptable results. Therefore, machine learning methods can be a promising solution to this problem. Methods: In this...