Portfolio

Overview:

This project focuses on predicting the number of spectators attending soccer matches based on historical data. The model is built using the Random Forest algorithm to analyze features such as match conditions and team performance, aiming to forecast attendance figures accurately. Model performance is validated using RMSE (Root Mean Squared Error).

Screenshots

Key Features:

1. Random Forest Model:

This model is used to predict soccer match attendance by analyzing a range of features, capturing both linear and non-linear relationships within the data for accurate forecasting.

2. Feature Extraction:

Key factors such as team performance, match importance, weather conditions, time of the match, and historical attendance data are extracted to improve the accuracy of predictions.

3. RMSE Validation:

The model’s accuracy is validated using Root Mean Squared Error (RMSE), which measures the differences between predicted and actual attendance figures, providing a reliable performance evaluation.

Category:

Tags:

Links:

• GitHub