Topsis Feature Choosing System
Project description
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!!!
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file Topsis-Harsh-101917088-2.0.1.tar.gz.
File metadata
- Download URL: Topsis-Harsh-101917088-2.0.1.tar.gz
- Upload date:
- Size: 3.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: 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
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9967df386a04086b31968b158a0dfad5c845b6637d7f49050955f55b764f1449
|
|
| MD5 |
8c24cf6350befb9c9954c0390bb2447f
|
|
| BLAKE2b-256 |
323bfe3ea1e56818515976ae1faba74c314e7a5b44ee304ad661e52f36ac8d58
|
File details
Details for the file Topsis_Harsh_101917088-2.0.1-py3-none-any.whl.
File metadata
- Download URL: Topsis_Harsh_101917088-2.0.1-py3-none-any.whl
- Upload date:
- Size: 4.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: 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
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
75d7ff0267c86119565a9840cd90078c30a55e474370bbb77b119083d29c0c32
|
|
| MD5 |
53040062d3b972347dd7efea45748439
|
|
| BLAKE2b-256 |
66ae886a81819f3fdef6b190cec6d4dd39c65f3fe240560e1f7541856dbd2799
|