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This is a topsis package of version 0.3

Project description

Topsis_Kunal_102053007

TOPSIS

Submitted By: Kunal Madan - 102053007.

Type: Package.

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

Version: 1.0.0.

Date: 2022-01-22.

Author: Kunal Madan.

Maintainer: Kunal Madan kmadan_bemba20@thapar.edu.

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


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-Kunal-102053007

In Command Prompt

topsis data.csv "1,1,1,1,1" "+,+,-,+,-" 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 0.66 0.44 4.9 32.9 9.73
M2 0.65 0.42 5 44.5 12.64
M3 0.61 0.37 3.3 41.1 11.35
M4 0.62 0.38 6.5 64.1 17.9
M5 0.83 0.69 6.4 34.4 10.58
M6 0.88 0.77 6.7 34.8 10.79
M7 0.63 0.4 4.5 39.1 11.16
M8 0.8 0.64 4.4 45.7 12.89

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 (out.csv)

Model P1 P2 P3 P4 P5 Topsis Score Rank
M1 0.66 0.44 4.9 32.9 9.73 0.21189353869415917 6
M2 0.65 0.42 5 44.5 12.64 0.3271776939542866 5
M3 0.61 0.37 3.3 41.1 11.35 0.15153299377397803 8
M4 0.62 0.38 6.5 64.1 17.9 0.5850881941527206 1
M5 0.83 0.69 6.4 34.4 10.58 0.49092824102735394 3
M6 0.88 0.77 6.7 34.8 10.79 0.5427136027309007 2
M7 0.63 0.4 4.5 39.1 11.16 0.2008035122309426 7
M8 0.8 0.64 4.4 45.7 12.89 0.48154813555267983 4

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

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