Supervised Machine Learning: A Survey

With the fast up-growth and evolution of new information and communication technologies and due to the factor of spread universal-connected objects, an ample amount of data has accumulated and become available for every individual or organization in the form of a set of big datasets. Today the world needs to exploit those big cumulated datasets to understand and interpret existent phenomena and other joint problems in different sectors (e.g., economic, health, education, and security) and enhance well-being by introducing intelligent and automatic processes and services. Artificial intelligence comes to answer those questions by leveraging the essential subfields like machine learning (ML) and deep learning. In this paper, we supply readers with a deep understanding of ML-based supervised learning (SL). We introduce machine learning in a general way and present its domains of application. After that, we discuss the popular SL-used algorithms and how to evaluate their performance. Then, we give a benchmark comparison based on our implementation of those algorithms in the field of heart-failure prediction.