Metadata-Version: 2.1
Name: TOPSIS-Yashwant-101803318
Version: 1.0.2
Summary: A Topsis package that takes inputs as CSV and generates scores in results CSV!
Home-page: https://github.com/meyash/TOPSIS_101803318
Author: Yashwant
Author-email: yashsn2127@gmail.com
License: UNKNOWN
Description: # TOPSIS_101803318
        
        ## TOPSIS method for multiple-criteria decision making (MCDM)
        
        ### 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.
        
        <br>
        
        ## INSTALLATION
        
        ```
        >> pip install TOPSIS_Yashwant_101803318
        ```
        
        ### USAGE
        
        ```
        >> topsis data.csv "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, R<sup>2</sup>, Root Mean Squared Error, Correlation, and many more.
        
        | Model | Correlation | R<sup>2</sup> | 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 (`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`.
        
        <br>
        
        ## Output file (result.csv)
        
        | Model | Correlation | R<sup>2</sup> | RMSE | Accuracy | Topsis_score | Rank |
        | ----- | ----------- | ------------- | ---- | -------- | ------------ | ---- |
        | M1    | 0.79        | 0.62          | 1.25 | 60.89    | 0.7722       | 2    |
        | M2    | 0.66        | 0.44          | 2.89 | 63.07    | 0.2255       | 5    |
        | M3    | 0.56        | 0.31          | 1.57 | 62.87    | 0.4388       | 4    |
        | M4    | 0.82        | 0.67          | 2.68 | 70.19    | 0.5238       | 3    |
        | M5    | 0.75        | 0.56          | 1.3  | 80.39    | 0.8113       | 1    |
        
        <br>
        The output file contains columns of input file along with two additional columns having **Topsis_score** and **Rank**
        
        ## License
        
        [![License](https://img.shields.io/badge/license-MIT-blue.svg)](/LICENSE)
        
        By [Yashwant](https://github.com/meyash)
        
        ## Contributors
        
        <img src="https://avatars3.githubusercontent.com/u/21121279?s=460&u=f0450278b2b569c4443ab8ee03f9dff7015da5bf&v=4" width="100px;" alt="toofff"/><br />
        
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        ## Version Guidance
        | ReDoc Release | OpenAPI Specification |
        |:--------------|:----------------------|
        | 1.0.2         | TOPSIS INIT           |
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
