This project implements a predictive model to estimate the weight of a fish based on various physical measurements such as length, height, and width. The predictive model is developed using Python and leverages machine learning techniques.
The dataset Fish.csv contains the following columns:
- Species: Species of the fish.
- Weight: Weight of the fish (target variable).
- Length1, Length2, Length3: Length measurements of the fish.
- Height: Height of the fish.
- Width: Width of the fish.
- Ensure you have Python and Jupyter Notebook installed on your system.
- Clone this repository: git clone https://github.com/feesh8/fish-weight-predictor.git
- Navigate to the project directory: cd fish-weight-predictor
- Run the Jupyter notebook: jupyter notebook
projet.ipynb - Follow the instructions in the notebook to explore the data, train the model, and make predictions.
| Model | Real MSE | Empirical MSE | Real R2 | Empirical R2 |
|---|---|---|---|---|
| Simple | 0.0051 | 0.0056 | 0.88 | 0.88 |
| Lasso Regulation | 0.0052 | 0.0057 | 0.88 | 0.88 |
| Polynomial expansion of degree 2 | 0.0009 | 0.0008 | 0.98 | 0.98 |