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A Python package to find TOPSIS for multi-criteria decision analysis method

Project description

TOPSIS-Python

Submitted By: Girik Garg 102003178


What is TOPSIS

Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) originated in the 1980s as a multi-criteria decision making method. TOPSIS chooses the alternative of shortest Euclidean distance from the ideal solution, and greatest distance from the negative-ideal solution. More details at wikipedia.


How to use this package:

TOPSIS-GIRIK-GARG-102003178 can be run as in the following example:

In Command Prompt to run the code:

topsis data.csv "1,1,1,1" "+,+,-,+" out.csv

Sample dataset

The decision matrix (a) should be constructed with each row representing a Model alternative, and each column representing a criterion like Fund Name , P1 ,P2 , P3 , P4 , P5.

Model Correlation R2 RMSE Accuracy
M1 0.8 0.64 3.5 37.5
M2 0.86 0.74 3.4 42.2
M3 0.69 0.48 5.7 70
M4 0.65 0.42 5.7 65.5
M5 0.9 0.81 6.6 39.1
M6 0.76 0.58 4 53.5
M7 0.69 0.48 6.2 51.3
M8 0.65 0.42 6 50.2

Output

Row_NO	Performance_score	Rank
1	    0.436737	         7
2	    0.389937	         8
3	    0.565650             4
4	    0.590487	         3
5	    0.522924	         5
6	    0.451344	         6
7	    0.637889	         1
8	    0.635536	         2


The rankings are displayed in the form of a table using a package 'tabulate', with the 1st rank offering us the best decision, and last rank offering the worst decision making, according to TOPSIS method.

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