Pythagorean Fuzzy Partial Correlation Measure and Its Application

The process of computing correlation among attributes an ordinary database is significant in the analysis and classification a data set. Due to uncertainties embedded classification, encapsulating techniques using Pythagorean fuzzy information appropriate curb uncertainties. Although coefficient between (PFD) applicable measure, its output not reliable because intrinsic effect other interfering PFD. fact that coefficients environment could remove PFD, notion partial measure (PFPCM) necessary enhance precise Because flexibility sets (PFSs), we are motivated initiate study on (PFPCC) based modified (PFCM). Examples given authenticate choice PFCM computational PFPCC. For application, discuss case pattern recognition proposed PFPCC after simple patterns technique. To be precise, contributions work include enhancement existing PFCC approach, development enhanced PFCC, application developed classifications.