Author : Dr. V.B.Narsimha 1
Date of Publication :18th April 2018
Abstract: Information Systems or databases holds enormous amounts of information/data which can be used for mining to extract the effective patterns which can be further used in making better decisions in business, healthcare, banking and other applications. During this research we tend to build a model which predicts the performance of a Student in a Programming Language named 'Python' based on the different factors like the high school marks, parent's education, nature of environment, faculty approach, difficulty level of subject, etc. During the research, we have applied different feature selection techniques using algorithms like Naive Bayes and Decision Tree and found that Naive Bayes have built a prediction model with accuracy of 82.4%. This model helps to understand about the students who may fail which in turn give a sign to faculty to focus on those students to take active measures in improving their performance.
Reference :
-
- NainjaRikh, 2015, Data Mining and Knowledge Discovery in Database, International Journal of Engineering Trends and Technology Volume 23 Number 2
- FestimHalili and AvniRustemi , International Journal of Computer Science and Mobile Computing, Vol.5 Issue.8,August - 2016 , pg.207 - 215
- C.R Kothari, 2006, Research Methodology Techniques, New Age International (P) Limited.
- Anne F. Maben, 2005, Chi- square test adapted from Statistics for the Social Sciences.
- Sebastian Nowozin, 2012, Improved Information Gain Estimates for Decision Tree Induction
- Jiang, Zhe, and Shashi Shekhar. “Spatial Information Gain-Based Spatial Decision Tree.” Spatial Big Data Science, 2017, pp. 57–76., doi: 10.1007/978-3-319- 60195-3_4