Mobile phones are one of the widely used communication platforms. It is also a much-preferred device to carry out various diverse activities in different sectors such as gaming, education, finance, the stock market, etc. Android operating system is one the most popularly used mobile operating system which requires mobile applications to perform any activity. Due to its open-source nature and large consumer market share, many illegitimate operations are targeted specifically through malware mobile applications. The objective of this paper is to obtain resilient features from Android APK files, to analyze the effectiveness of various machine learning classifiers, to perform hyperparameter tuning to find the appropriate parameters of the classifiers that improve the evaluation metrics, and to handle the imbalance issue in the dataset using various imbalance approaches.