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Compute Topsis scores and ranks for a given csv file using topsis method for multiple-criteria decision making(MCDM)

Project description

Topsis-Shrey-102183040

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-Shrey-102183040

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 line arguement topsis 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

© 2023 Shrey Saxena

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

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