Predictive Analysis Tool for Predicting Student Performance and Placement Performance using ML algorithms.

摘要: Recently, Predictive Analysis using machine learning and data science has had greater growth in almost every field. analysis for predicting student performance always been difficult than other predictions such as House price prediction, stock market sales etc., Due to the difficulty finding collecting appropriate datasets, especially college-level education. Since grading system differs from universities universities, it is even more collect proper datasets that can be used a global dataset, created based on common university. In this paper, we have taken task which contains details of over 185 students. The dataset was collected SRM Valliammai engineering college, includes 2018 2019 passed out Other academic data, also covers attributes around 20 would improve accuracy score. Using our aim develop training model predicts final CGPA placement result particular student. We successfully predicted student’s their result. results algorithms like Linear Regression (LR1), Decision tree (DT) algorithm, K-nearest neighbor algorithm (KNN), Logistical regression (LR2) Lasso (LR3) algorithm. And obtained excellent with 94%. are comparing score above-given algorithms. one highest displayed output.