This package is for TOPSIS
Project description
TOPSIS
Code by: Sheramir
## What is TOPSIS
TOPSIS stands for ‘The Technique for Order of Preference by Similarity to the Ideal Solution’ is a multi-criteria decision analysis(MCDA) method. It is a method of compensatory aggregation that compares a set of alternatives by identifying weights for each criterion, normalising scores for each criterion and calculating the geometric distance between each alternative and the ideal alternative, which is the best score in each criterion.
How to run
Before running, make sure you have pandas installed on your system
Open Terminal and input the following commands
pip install TOPSIS_Sheramir_101803549
To get started quickly, just use the following:
from TOPSIS_Sheramir_101803549.topsis import topsis
topsis('inputfilename','Weights','Impacts','Outputfilename')
make ensure the weights and impacts should be in ""
eg: "1,1,1,1" and "+,-,+,-"
Pre-requisite
The data should be enclosed in the csv file. There must be more than 2 columns
Result
the output(outputfilename) is saved in the project folder with extra 2 columns with topsis score and rank.
Sample Input
This input was used to test the module
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 |
Output
Model | Corr | Rseq | RMSE | Accuracy | Topsis Score | Rank |
---|---|---|---|---|---|---|
M1 | 0.79 | 0.62 | 1.25 | 60.89 | 0.639133 | 2.0 |
M2 | 0.66 | 0.44 | 2.89 | 63.07 | 0.212592 | 5.0 |
M3 | 0.56 | 0.31 | 1.57 | 62.87 | 0.407846 | 4.0 |
M4 | 0.82 | 0.67 | 2.68 | 70.19 | 0.519153 | 3.0 |
M5 | 0.75 | 0.56 | 1.3 | 80.39 | 0.828267 | 1.0 |
License
© 2020 Sheramir
This repository is licensed under the MIT license. See LICENSE for details.
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