topsis implementation
Project description
Introduction
TOPSIS( Technique for order for preference by similarity to Ideal solution ) for MCDM (Multiple criteria decision making) in Python compiled by PRACHI KUMAR, 102103419 , TIET, Patiala.
Installation
pip install TOPSIS_102103419
License
©2024 Prachi Kumar This repository is licensed under the MIT license. See LICENSE for 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_102103419-0.0.1.tar.gz.
File metadata
- Download URL: TOPSIS_102103419-0.0.1.tar.gz
- Upload date:
- Size: 2.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.12.1
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
a05d6f9bdce19bfdbdc292d123099b4d3d5034afcf25bf30b6c602b4b69eed89
|
|
| MD5 |
7f23b2906dba0e878a0bd12733165b2e
|
|
| BLAKE2b-256 |
d0f169cdbaf4706743edc55724a982a71c147e36dfc77e8fa4ec716617288245
|
File details
Details for the file TOPSIS_102103419-0.0.1-py3-none-any.whl.
File metadata
- Download URL: TOPSIS_102103419-0.0.1-py3-none-any.whl
- Upload date:
- Size: 2.3 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.12.1
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
bb2408ff5f2fd4939e3a5c3ff94ee7d034ba1d4288ac83e908b8433b4e4fa8b3
|
|
| MD5 |
4a3f9f53b8206f6941511e5917d377f9
|
|
| BLAKE2b-256 |
156336baa801ceaeac31bd5d6b5445e5f89db1b2e7024761d1ce37d45c0cb260
|
