The vast landscape of mobile applications, user ratings play a crucial role in determining an app's success and popularity. Predicting these ratings accurately not only aids users in making informed decisions but also assists developers in improving their apps. This paper presents an efficient machine learning technique tailored for rating prediction of Google Play Store apps. Our approach leverages a combination of advanced machine learning algorithms, feature analysis, and data pre-processing methods to achieve robust performance. Simulation results shows that the effectiveness of proposed technique through extensive experimentation on datasets, showcasing its ability to accurately forecast app ratings....
Authors: Veena Vadinee Raikwar, Prof. Mahendra Sahare, Prof. Anurag Shrivastava.