sscore

Standardizer of raw scores
10 Downloads
Updated 25 Jan 2018

View License

sscore transform scores in the inputed evalution matrix (S) to normalized scale via following methods:
'sum' - Normalize scores via a1=Sij/Sigma(Sij)
'max' - Normalize scores via a2=Sij/Max
'minmax' - Normalize scores via a3=(Sij-Min)/(Max-Min)|a3=(Sij-Max)/(Min-Max)
'sigma' - Normalize scores via a4=Sij/Square(Sum(Sij)²)
'rs' - Normalize scores via a5=N-ri+1/Sigma(N-ri+1)
're' - Normalize scores via a6=(N-ri+1)^p/Sigma(N-ri+1)^p
'rr' - Normalize scores via a7=(1/ri)/Sigma(1/ri)
'roc' - Normalize scores via a8=(1/N)*Sigma(1/ri)
------------------------------------------------------
'rs' :Rank Sum weight method
're' :Rank Exponent weight method
'rr' :Rank Reciprocal weight method
'roc' :Rank-Order Centroid weight method

Cite As

Mahdi Shakhesi (2026). sscore (https://www.mathworks.com/matlabcentral/fileexchange/65833-sscore), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2017a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Categories
Find more on Statistics and Machine Learning Toolbox in Help Center and MATLAB Answers
Version Published Release Notes
1.0.0.0