Merge pull request #13 from UBC-MDS/project_structure

Project structure setup

CONDUCT.md

@@ -34,7 +34,7 @@ This Code of Conduct applies both within project spaces and in public spaces whe
 
 ## Enforcement
 
-Instances of abusive, harassing, or otherwise unacceptable behavior may be reported by contacting the project team. The project team will review and investigate all complaints, and will respond in a way that it deems appropriate to the circumstances. The project team is obligated to maintain confidentiality with regard to the reporter of an incident. Further details of specific enforcement policies may be posted separately.
+Instances of abusive, harassing, or otherwise unacceptable behavior may be reported by contacting the project team at [email protected], [email protected], [email protected] and [email protected]. The project team will review and investigate all complaints, and will respond in a way that it deems appropriate to the circumstances. The project team is obligated to maintain confidentiality with regard to the reporter of an incident. Further details of specific enforcement policies may be posted separately.
 
 Project maintainers who do not follow or enforce the Code of Conduct in good faith may face temporary or permanent repercussions as determined by other members of the project's leadership.
 

README.md

@@ -2,6 +2,22 @@
 
 A package providing functions to calculate key regression metrics: R-squared, Mean Absolute Error (MAE), Mean Squared Error (MSE), and Mean Absolute Percentage Error (MAPE).
 
+## Features
+
+This package consists of four functions:
+- `r_squared`:
+    - This function calculates the R-squared of the model, which measures how well the model explains the variation in the data. 
+- `mean_absolute_error`: 
+    - This function finds the average difference between predicted and actual values.
+- `mean_squared_error`:
+    - This function calculates the average of the squared differences between predictions and actual values. 
+- `mean_absolute_percentage_error`:
+    - This function shows prediction error as a percentage, making it easy to understand.
+
+##  matrics_calculator in the Python Ecosystem
+
+`matrics_calculator` works alongside Python libraries like `scikit-learn` by providing simple implementations of regression metrics. Unlike `scikit-learn`’s full toolkit for modeling and evaluation, this package focuses only on metrics, making it easy to use for quick analysis or custom workflows.
+
 ## Installation
 
 ```bash
@@ -23,3 +39,10 @@ Interested in contributing? Check out the contributing guidelines. Please note t
 ## Credits
 
 `matrics_calculator` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
+
+## Constributors
+
+- Celine Habashy
+- Jay Mangat
+- Yajing Liu
+- Zhiwei Zhang