Author(s)

Zhenhang Wang, Xiaomeng Wei, Jilin Yang

Corresponding Author

Zhenhang Wang

Abstract

Machine learning is a multi-disciplinary subject that has emerged over the past 20 years and involves many disciplines such as probability theory, statistics, approximation theory, analytical theory, and computational complexity theory. Machine learning theory is primarily about designing and analyzing algorithms that allow computers to automatically “learn”. Machine learning algorithms are a class of algorithms that automatically analyze and obtain rules from data and use rules to predict unknown data. Because learning algorithms involve a large number of statistical theories, machine learning is particularly closely related to inferred statistics, also known as statistical learning theory. In terms of algorithm design, machine learning theory focuses on achievable, effective learning algorithms. Many inference problems are difficult to follow without program, so part of the machine learning research is to develop an approximation algorithm that is easy to handle.

Keywords

Data, Data mining, Machine learning, Technology applications