Advances in DEA and ML Methodologies

Abstract

In a world where data processing is influential for ASC decisions, the introduction of DEA and ML as approaches to ASC performance measurement and analysis is an achievement. Data Envelopment Analysis (DEA) is a mathematical linear programming technique used to evaluate the efficiency of Decision Making Units (DMUs) with an intention of increasing efficiency of organisations in both private and public domains. However, when a new DMU has to be evaluated, the efficiency score has to be recalled, particularly today they re-conducted the DEA analysis with large number of samples available in many field of study in the real world which seems to be time consuming and needs a very large amount of computations. DEA has thousands of applications in various fields for evaluating the efficiency of the Decision Making Units and ML is the modern technology in model predictive and data analysis filed.