Rain Tomorrow Prediction

Overview

This project implements a predictive model to forecast whether it will rain tomorrow based on historical weather data. The dataset used is weather.csv, which includes various weather parameters.

Features

• Logistic Regression model for predicting rainfall.
• Performance evaluation using a confusion matrix and accuracy metrics.
• Visualization of the confusion matrix as a heatmap for better interpretability.

How to Run the Code

To run this project, follow these steps:

1. Install Python on your system if you haven't already.
2. Download the dataset (weather.csv) and place it in the same directory as the Python code.
3. Run the code in your command line by executing:

   python path/to/your/script.py

Output

Confusion Matrix and Accuracy

Upon running the code, you will see the confusion matrix and accuracy displayed in the terminal.

Heatmap of Confusion Matrix

A heatmap visualization of the confusion matrix will also be generated for a more intuitive understanding of the model's performance.

Technologies Used

• Python
• Pandas
• Sci-kit Learn
• Matplotlib
• Seaborn

Conclusion : This project showcases the application of logistic regression for binary classification in weather prediction, demonstrating fundamental skills in data analysis and machine learning.