TOPSIS-Python
Topsis : UCS538
Submitted By: Jayati Gumber - 101803546
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. More details at wikipedia.
How to use this package:
TOPSIS-Jayati-101803546 can be run as in the following example:
In Command Prompt
>> topsis data.csv "1,1,1,2" "+,+,-,+"
Sample dataset
The decision matrix (a) 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 | Correlation | R2 | 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 |
Weights (w) is not already normalised will be normalised later in the code.
Information of benefit positive(+) or negative(-) impact criteria should be provided in I.
The rankings are displayed in the form of a table using a package 'tabulate', with the 1st rank offering us the best decision, and last rank offering the worst decision making, according to TOPSIS method.
1 maintainer
Metadata
1 maintainer
Release files for TOPSIS-Jayati-101803546 1.0.0
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Release files / TOPSIS_Jayati_101803546-1.0.0-py3-none-any.whl
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