Football Match Prediction using Random Forest Classifier

This study explores the difficulty of applying the Random Forest Algorithm to predict football outcomes. The application and modification of the Random Forest method, with a focus on improving prediction accuracy and efficiency, is the aim of this study. Key algorithm parameters, such as min_sample_split and min_sample_leaf, are adjusted and contrasted throughout this study to determine their influence on the accuracy of predictions. The painstaking optimization of these variables led to the discovery of an ideal combination, significantly strengthening the algorithm's capacity for precise football match prediction.