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.
pip install TOPSIS-Anubhav-101803051
Input file contain three or more columns
First column is the object/variable name
From 2nd to last columns contain numeric values only
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.
| 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 |
| 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 |
© 2020 Anubhav Sharma
This repository is licensed under the MIT license. See LICENSE for details.