Performance Based Machine Learning Model to Enhance Performance of Students 
Bhavesh Patel
Dr. Bhavesh Patel, Assistant professor, Department of Computer Science Ganpat University, MCA,
Manuscript received on January 08, 2021. | Revised Manuscript received on January 15, 2021. | Manuscript published on February 28, 2021. | PP: 1-4 | Volume-10 Issue-4, February 2021 | Retrieval Number: 100.1/ijitee.D84290210421 | DOI: 10.35940/ijitee.D8429.0210421
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Machine learning techniques are used by many organizations to analyze the data and finding some meaningful hidden pattern from the data, this process is useful by an organization to take the decision making process. Various organizations used like marketing, health care, software organization and education institute etc used it in decision making. We have used machine learning techniques to enhance the performance of students. It will be ultimately used by educational institute to improve the status of educational institute. This research paper includes Naïve Bayes (NB), Logistic Regression (LR), Artificial Neural Network(ANN) and Decision Tree machine learning techniques. Performance of these models have been compared using accuracy measures parameters and ROC index. This research paper has used various parameters like academic performance and demographic information to build the model. In addition to judge the performance also used some additional parameters to measure the performance like F-measure, precision, error rate and recall. The dataset is collected using survey methodology to build the model. As a conclusion found that the Artificial Neural Network model get the best performance among all the models.
Keywords: Machine learning, Precision, Recall, Naïve Bayes, Artificial Neural Network, Classification, performance.