Volume 18, No. 6, 2021

Teacher Learning Algorithm And Linear Regression Based Student Grade Prediction For IT Course



Data of any field is good source of information for analysis of any happening. This analysis lead to the development of prediction model as well. Student of school / college depends on instructor observation, many of researchers are working to optimize this work by different mining techniques. This paper has developed grade prediction model for IT course analysis of college student pursing professional degrees. Student has variety of features that directly or indirectly affects its grade. So selection of optimize feature set is done by teacher learning genetic algorithm. Dynamic nature of teacher learning algorithm increase flexibility of work to select features without any guidance. Selected features were used for the training of linear regression model. Trained model takes student feature as input predict grade of student. Experiment was done on real dataset collect from Madhya Pradesh IT college. Result shows that proposed model has increase the grade prediction accuracy of the work.

Pages: 3110-3119

Keywords: Data Analysis, Feature Selection, Neural Network, Genetic Algorithm.

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