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Incident Prediction and Police Allocation Model

Overview

This project predicts incident counts using a RandomForest model based on the month, district, and neighborhood. The model utilizes features such as time (encoded month or hour), normalized incident counts, and cluster information derived from K-means clustering, along with categorical data like police districts and neighborhoods.

Getting Started

You can find our app running at https://policeallocation.streamlit.app/

For running this repository locally

Prerequisites

Ensure you have the following installed:

  • Python 3.7+
  • pandas
  • numpy
  • scikit-learn
  • streamlit
  • joblib

You can install the necessary libraries using pip:

pip install pandas numpy scikit-learn streamlit
git clone https://github.com/your-username/your-repository.git

cd your-repository

Usage

To run the Streamlit application: streamlit run app.py

Navigate to http://localhost:8501 in your web browser to interact with the app.

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