TOPSIS_Harsh_101917088
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
How to use this package? First you have to install the package name 'Topsis-Harsh-101917088' using the following command:
'''pip install TOPSIS_Harsh_101917088'''
{If it doesn't work use version after above command}
How to use it?
Open terminal and type PYTHON TOPSIS along with input file path whose topsis value and rank you wanted to find i.e python TOPSIS "data.csv"
##Arguments Required: (Assumne we have 3 attributes in dataset.) You have to required one .csv file. (101917118-data.csv) Pass weights to each attribute. (e.g.: [1,1,1]) Pass impacts to each attribute. (e.g.: [+,-,+]) Pass the name of the file with you want to put on .csv file. (101917118-result.csv)
Give arguments like Example python 101556.py 101556-data.csv “1,1,1,2” “+,+,-,+” 101556-result.csv
Please make sure to update tests as appropriate.
##Github Link https://github.com/Harsh23Kashyap/Predictive-Analysis/tree/main/Assignment4%20-%20Topsis/Solution
##Happy Coding!!!
Metadata
Release files for Topsis-Harsh-101917088 2.0.1
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Source distribution (sdist)
| File | Size | Uploaded | |
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| Topsis-Harsh-101917088-2.0.1.tar.gz | 3.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| Topsis_Harsh_101917088-2.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 8.0 kB
Release files / Topsis-Harsh-101917088-2.0.1.tar.gz
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Release files / Topsis_Harsh_101917088-2.0.1-py3-none-any.whl
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| Size | 4.1 kB |
| Tags | Python 3 |
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twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.26.0 requests-toolbelt/0.9.1 urllib3/1.26.7 tqdm/4.62.3 importlib-metadata/4.11.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.9.7
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