The use of applications is part of people daily lives for various activities. In relation to development, the curiosity about the characteristics responsible for success arises. We use classifiers to meet the success requirements of the Google Play Store app store. Through the techniques of KNN and Random Forest, a statistical analysis was done performing the regressions of the applications according to some characteristics: as hypothesis test, correlation and regression metrics analysis. This work aims to create inference engines, allowing the prediction of application ratings, using the KNN and Random Forest regression techniques. The Random Forest showed better results than the KNN.

中文翻译：

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应用数据挖掘技术对 Google Play 商店应用程序进行评分预测


应用程序的使用是人们日常生活中各种活动的一部分。就发展而言，人们对成功的特征产生了好奇。我们使用分类器来满足 Google Play Store 应用商店的成功要求。通过 KNN 和随机森林技术，根据一些特征对应用程序进行回归分析：假设检验、相关性和回归指标分析。这项工作旨在创建推理引擎，使用 KNN 和随机森林回归技术来预测应用程序评级。随机森林显示出比 KNN 更好的结果。