1.1 KiB
1.1 KiB
Model Information
Overview
The Test Score Predictor uses a Linear Regression machine learning model trained to predict test scores based on the number of hours studied.
Model Details
- Model Type: Linear Regression
- Features Used:
- Hours_Studied: Number of hours a student studied
- Output: Predicted test score
- Model File:
linear_regression_model.pkl - Scaler File:
scaler.pkl
Dataset
The model was trained on a dataset containing information about students' study hours and their corresponding test scores.
Model Performance
The model demonstrates a strong correlation between hours studied and test scores, with typical metrics showing:
- R² score: ~0.95
- Mean Absolute Error: ~2-3 points
Limitations
- The model assumes a linear relationship between study hours and test scores
- The model may not account for other factors that influence test performance (quality of study, prior knowledge, etc.)
- Predictions for very low or very high study hours may be less reliable
- The model is intended for educational purposes and should not be used for critical decision-making