# Model Information

## Overview

The Streamlit 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