Topsis-Pulkit-102003619 1.0.0

A Python package implementing TOPSIS technique.

Topsis-Pulkit-102003619

Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) originated in the 1980s as a multi-criteria decision making method. It is based on the fundamental premise that the best solution has the shortest distance from the positive-ideal solution, and the longest distance from the negative-ideal one. Alternatives are ranked with the use of an overall index calculated based on the distances from the ideal solutions.

Installation

pip install Topsis-Pulkit-102003619

OR alternatively use

python -m pip install Topsis-Pulkit-102003619

How to use it?

Topsis-Pulkit-102003619 can be used as

In Terminal

Provide the file containing data in CSV Format, Provide corresponding weights and Impacts topsis data.csv "1,0.5,1,0.5" "+,-,+,-" Output.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.

License

© 2023 Pulkit

This repository is licensed under the MIT license. See LICENSE for details.