smlkg/mammals-sleeping-prediction

Predicting Sleeping Variables in Mammals

This project aims to develop predictive models for estimating sleeping variables in mammals. The dataset comprises various features related to mammalian behavior and physiology, with the target variable being sleeping patterns. Three different modeling approaches are explored: Ordinary Least Squares (OLS) regression, Random Forest, and Gaussian Naive Bayes.

Dataset Description

The dataset contains observations of sleeping variables in mammals, along with features such as physiological measurements, environmental factors, and behavioral indicators. Each observation represents a mammalian species, and the target variable is the sleeping pattern, categorized into different classes based on duration, quality, and other characteristics.

Folder Structure:

• 0_Dataset.csv/: Contains the original dataset.
• 1_Density per Spices.csv/: Contains the density per spices dataset.
• 2_Mammal_Functional Data.csv/: Contains the additional mammal functional dataset.
• 3_Amniote_Database.csv/: Contains the amniote dataset.
• Predicting_Sleep_Variables_in_Mammals.ipynb/: Includes Python scripts for data preprocessing, model training, and evaluation.
• requirements.txt/ Contains the packages needs to run the project
• README.md: Provides project overview, setup instructions, and usage guidelines.

Dependencies

• Jupyter Notebook (.ipynb)
• Python 3.10.12
• Numpy 1.25.2
• Pandas 1.5.3
• Matplotlib 3.7.1
• Seaborn 0.13.1
• Scipy 1.11.4
• Scikit-learn
• Statsmodels 0.14.1

Executing program

1. Open the files in Google Colab or Anaconda Jupyter Notebook
2. Install the requirements.txt
3. Import the dataset to the notebook
4. You're good to go!

$ pip install -r requirements.txt

Authors

Contributors names and contact info

• Samuel Kong (https://github.com/smlkg)
• Théo Ourvoie (https://github.com/Theo-Ou)
• Garam Baek (https://github.com/garambaek)
• Lucas Favero (https://github.com/Lucas-Favero)

License

This project is licensed under the MIT License. See the LICENSE file for more details.