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version (1.96 KB) by Mahdi Shakhesi
Standardizer of raw scores


Updated 25 Jan 2018

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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 (2021). sscore (, MATLAB Central File Exchange. Retrieved .

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MATLAB Release Compatibility
Created with R2017a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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