Principle Component Evaluation for Analyzing the Design Trends in Fashion Industry

Abstract

Principle component analysis has its applications in many fields like finance, data mining, psychology, bio information, etc., as it is used to find patterns by reducing the dimensions of the data. The following paper proposes an idea to apply Principle Component Analysis  (PCA) on the attributes of the clothes collected in a synthetic dataset to predict the class of the most used designs, colours, patterns, fabrics, etc. to design new clothes. This will assist the designers to design models that are most liked by the people thus increasing the sales with less effort and investment.