topsis-102103357 0.0.4

Comparison of models using Topsis

Introduction

TOPSIS (technique for order performance by similarity to ideal solution) is a useful technique in dealing with multi-attribute or multi-criteria decision making (MADM/MCDM) problems in the real world.

Installation

Use the package manager pip to install.

pip install topsis-102103357

Usage

Enter csv filename followed by .csv extentsion, then enter the weights vector with vector values separated by commas, followed by the impacts vector with comma separated signs (+,-) and enter the output file name followed by .csv extension.

topsis-102103357 [InputDataFile as .csv] [Weights as a string] [Impacts as a string] [ResultFileName as .csv]

Sample Input

Fund Name	P1	P2	P3	P4	P5
M1	0.84	0.71	6.7	42.1	12.59
M2	0.91	0.83	7	31.7	10.11
M3	0.79	0.62	4.8	46.7	13.23
M4	0.78	0.61	6.4	42.4	12.55
M5	0.94	0.88	3.6	62.2	16.91
M6	0.88	0.77	6.5	51.5	14.91
M7	0.66	0.44	5.3	48.9	13.83
M8	0.93	0.86	3.4	37	10.55

topsis-102103357 data.csv "1,1,1,1,1" "+,-,+,-,+" output.csv

Sample Output

Results saved to output.csv

Fund Name	P1	P2	P3	P4	P5	Performance	Rank
M1	0.84	0.71	6.7	42.1	12.59	0.404268469809145	5.0
M2	0.91	0.83	7	31.7	10.11	0.699297825503612	1.0
M3	0.79	0.62	4.8	46.7	13.23	0.333581741928051	8.0
M4	0.78	0.61	6.4	42.4	12.55	0.364968017290041	6.0
M5	0.94	0.88	3.6	62.2	16.91	0.534831688649816	2.0
M6	0.88	0.77	6.5	51.5	14.91	0.439693012540145	4.0
M7	0.66	0.44	5.3	48.9	13.83	0.526356720373482	3.0
M8	0.93	0.86	3.4	37	10.55	0.341972356097968	7.0

The best model is M2

License

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