Topsis-Ritwik-101917131 1.2.0

Package to calculate Topsis Score and Rank them accordingly

Topsis_Ritwik

TOPSIS

Created By: Ritwik Khanna. Type: Package.

Title: TOPSIS method for multiple-criteria decision making (MCDM).

Version: 1.2.0.

Author: Ritwik Khanna.

Maintainer: Ritwik Khanna [e-mail]>.

Description: Evaluation of alternatives based on multiple criteria using TOPSIS method..

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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.

How to install this package:

>> pip install Topsis-Ritwik-101917131

In Command Prompt

>> python topsis.py data.csv "1,1,1.5,1,2" "+,+,-,+,-" result.csv

Input file (data.csv)

The decision matrix should be constructed with each row representing a Model alternative, and each column representing a criterion like Accuracy, R², Root Mean Squared Error, Correlation, and many more.

Model	P1	P2	P3	P4	P5
M1	0.84	0.71	6.7	42.1	12.59
M2	0.91	0.83	7.0	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	37.0	10.55

Weights (weights) is not already normalised will be normalised later in the code.

Information of benefit positive(+) or negative(-) impact criteria should be provided in impacts.

Output file (result.csv)

Model	P1	P2	P3	P4	P5	Topsis Score	Rank
M1	0.84	0.71	6.7	42.1	12.59	0.4295	5
M2	0.91	0.83	7.0	31.7	10.11	0.5055	4
M3	0.79	0.62	4.8	46.7	13.23	0.5358	3
M4	0.78	0.61	6.4	42.4	12.55	0.4185	6
M5	0.94	0.88	3.6	62.2	16.91	0.5616	2
M6	0.88	0.77	6.5	51.5	14.91	0.3983	8
M7	0.66	0.44	5.3	48.9	13.83	0.4134	7
M8	0.93	0.86	3.4	37.0	10.55	0.7332	1

The output file contains columns of input file along with two additional columns having **Topsis_score** and **Rank**