HANEEF04/student-scholarship-predictor

Student Scholarship Predictor

A machine learning web application that predicts whether a student will receive a scholarship based on their academic performance and personal attributes.

Dataset

The model is trained on a student performance dataset containing 6,008 records with the following features:

• —Math Score — score out of 100
• —Science Score — score out of 100
• —English Score — score out of 100
• —Attendance Percentage — percentage of classes attended
• —Age — student age (17–30)
• —Gender — Male, Female, or Other
• —Department — CS, IT, ECE, MECH, or CIVIL

The target variable is Scholarship (Yes / No). One record with a missing Scholarship value is dropped during preprocessing.

Model

A Random Forest Classifier trained with:

• —n_estimators=200
• —max_depth=5
• —min_samples_leaf=10
• —class_weight="balanced" to handle class imbalance
• —80/20 stratified train/test split with random_state=42

Label encoders are applied to Gender, Department, and Scholarship before training.

Usage

Adjust the sliders and selectors to match a student's profile, then click Predict to get a Yes/No scholarship prediction with confidence score and probability breakdown.