A New Importance-Performance Analysis by Size-Insensitive Integrity-Based Fuzzy C-Means

摘要

In conventional Importance-Performance Analysis, lots of researchers assume that a given set of attributes is spread across four quadrants. The researcher uses the vertical axis and the horizontal axis on the drawing to optimally divide the quadrants. From the perspective of machine learning, a new Importance-Performance Analysis by Size-Insensitive Integrity-based Fuzzy C-Means is pro-posed. From the empirical results, the new IPA by Size-Insensitive Integrity-based Fuzzy C-Means is plain and simple, successful, and easy to know.