Abstract

In this research, we develop a machine learning model to predict the ratings of Google Play Store applications using a comprehensive dataset. Our approach includes extensive data preprocessing, feature engineering, and model optimization using Random Forest Regressor and ensemble methods. The proposed model demonstrates significant improvements in prediction accuracy, emphasizing the importance of advanced preprocessing techniques and ensemble learning in regression tasks