TOPSIS-Anubhav-101803051 1.0.1

Compute Topsis Scores/Ranks of a given csv file

TOPSIS-Anubhav-101803051

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.

Installation

pip install TOPSIS-Anubhav-101803051
OR
pip3 install TOPSIS-Anubhav-101803051

Input csv format

Input file contain three or more columns
First column is the object/variable name
From 2nd to last columns contain numeric values only

How to use it

Command Prompt
topsis <InputDataFile> <Weights> <Impacts> <ResultFileName>
Example:
topsis inputfile.csv “1,1,1,2” “+,+,-,+” result.csv

Note: The weights and impacts should be ',' seperated, input file should be in pwd.

Sample input data

Model	Corr	Rseq	RMSE	Accuracy
M1	0.79	0.62	1.25	60.89
M2	0.66	0.44	2.89	63.07
M3	0.56	0.31	1.57	62.87
M4	0.82	0.67	2.68	70.19
M5	0.75	0.56	1.3	80.39

Sample output data

Model	Corr	Rseq	RMSE	Accuracy	Topsis Score	Rank
M1	0.79	0.62	1.25	60.89	0.7731301458119156	2
M2	0.66	0.44	2.89	63.07	0.22667595732024362	5
M3	0.56	0.31	1.57	62.87	0.4389494866695491	4
M4	0.82	0.67	2.68	70.19	0.5237626971836845	3
M5	0.75	0.56	1.3	80.39	0.8128626132980138	1

License

© 2020 Anubhav Sharma

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