Classifier Optimization Using Genetic Algorithm in a Web based Educational System
نویسندگان
چکیده
The main aim of this paper is to introduce to find similar patterns of use in the data gathered from Learning Online Network with Computer-Assisted Personalized Approach (LON-CAPA), and eventually be able to make predictions as to the most-beneficial course of studies for each learner based on their present usage. The system could then make suggestions to the learner as to how to best proceed. The objective is to predict the students’ final grades based on their web-use features, which are extracted from the homework data. Using a GA to optimize a combination of classifiers test data we selected the student and course data of a LON-CAPA course, we design, implement, and evaluate a series of pattern classifiers with various parameters in order to compare their performance on a dataset from LON-CAPA. Keywords—Data Mining, Genetic Algorithm, Clustering, Classification, Prediction.
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