Читать книгу Data Analytics in Bioinformatics - Группа авторов - Страница 14

Rajat Verma, Vishal Nagar and Satyasundara Mahapatra*

PSIT, Kanpur, Uttar Pradesh, India

Abstract

Artificial Intelligence (AI) has enhanced its importance through machines in the field of present business scenario. AI delineates the intelligence illustrated by machines and performs in a contrasting manner to the natural intelligence signified by all living objects. Today, AI is popular due to its Machine Learning (ML) techniques. In the field of ML, the performance of a machine depend upon the learning performance of that machine. Hence, the improvement of the machine’s performance is always proportional to its learning behavior. These Learning behaviors are obtained from the knowledge of living object’s intelligence. An introductory aspect of AI through a detailed scenario of ML is presented in this chapter. In the journey of ML’s success, data is the only requirement. ML is known because of its execution through its diverse learning approaches. These approaches are known as supervised, unsupervised, and reinforcement. These are performed only on data, as its quintessential element. In Supervised, attempts are done to find the relationship between the independent variables and the dependent variables. The Independent variables are the input attributes whereas the dependent variables are the target attributes. Unsupervised works are contrary to the supervised approach. The former (i.e. unsupervised) deals with the formation of groups or clusters, whereas the latter (i.e. supervised) deals with the relationship between the input and the target attributes. The third aspect (i.e. reinforcement) works through feedback or reward. This Chapter focuses on the importance of ML and its learning techniques in day to day lives with the help of a case study (heart disease) dataset. The numerical interpretation of the learning techniques is explained with the help of graph representation and tabular data representation for easy understanding.

Keywords: Artificial intelligence, machine learning, supervised, unsupervised, reinforcement, knowledge, intelligence