In order to classify a web page as being benign or malicious, we designed 14 basic and 16 extended features. The basic features that we implemented were selected to represent the essential characteristics of a web page. The system heuristically combines two basic features into one extended feature in order to effectively distinguish benign and malicious pages. The support vector machine can be ...

In this thesis, a multi-source system for human identification is developed. The system uses three sources: face classifier, height classifier, and color classifier. In the process of developing this system, classifier combination and the integration of classifer outputs over sequences of data points were studied in detail. The method of classifier combination used relies on weighing classifier...

Mean Field Genetic Algorithm (MGA) is a hybrid algorithm of Mean Field Annealing (MFA) and Simulated annealing-like Genetic Algorithm (SGA). It combines benefit of rapid convergence property of MFA and effective genetic operations of SGA. This paper presents an approach for building a multi-classifier system in a MGA-based inductive learning environment. Multiple base classifiers are combined t...

In this paper, we present our supervised learning approach to coreference resolution in ConLL corpus. The system relies on a maximum entropy-based classifier for pairs of mentions, and adopts a rich linguisitically motivated feature set, which mostly has been introduced by Soon et al (2001), and experiment with alternaive resolution process, preprocessing tools,and classifiers. We optimize the ...

This thesis presents an implementation of a learning classifier system which learns good database schema. The system is implemented in Java using the NetBeans development environment, which provides a good control for the GUI components. The system contains four components: a user interface, a rule and message system, an apportionment of credit system, and genetic algorithms. The input of the s...

After harvesting wheat, the main concern is classifying wheat seeds according to their quality, size, variety and etc. there are different procedures to measure parameters and analyzing wheat seeds but they are time-consuming and error-prone. An automated system is developed being capable to analyze and classify wheat seeds faster with higher confidence level based on defined attributes, the sy...

Learning Classifier Systems use evolutionary algorithms to facilitate rule-discovery, where rule fitness is traditionally payoff based and assigned under a sharing scheme. Most current research has shifted to the use of accuracy-based fitness, after the introduction of XCS, where rule fitness is based on a rule's ability to predict the expected payoff from its use. Whilst XCS has been shown to ...

Classifier systems are production rule systems that automatically generate populations of rules cooperating to accomplish desired tasks. The genetic algorithm is the systems' discovery mechanism, and its effectiveness is dependent in part on the accurate estimation of the relative merit of each of the rules (classifiers) in the current population. Merit is estimated conventionally by use of the...