About this document
Feature Extraction for Student Performance by suchitragude is a document available to read on EtoBox.
The document presents a project on classifying students based on their academic performance using feature extraction and machine learning techniques. It highlights the drawbacks of existing systems, such as high manpower and paperwork, while proposing a more efficient solution that saves time and is easy to use. The study concludes that Gradient Boosting and Random Forest classifiers are the most effective methods for predicting student performance.
- Author
- suchitragude
- Language
- EN