Skip to main content

Multi-Criteria Decision Making

Project description

TOPSIS

Submitted By: Pramit Deep Kaur - 101903198.

Type: Package.

Title: TOPSIS method for multiple-criteria decision making (MCDM).

Version: 1.0.0.

Date: 2022-02-26.

Author: Pramit Deep Kaur Gogna.

Maintainer: Pramit Deep Kaur Gogna pramitdkgogna@gmail.com.

Description: Evaluation of alternatives based on multiple criteria using TOPSIS method..


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. It is a method where multiple models can be compared and scores can be assigned accordingly.


How to install this package:

>> pip install TOPSIS-Yash-101803064

In Command Prompt

>> 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, R2, Root Mean Squared Error, Correlation, and many more.

Model Correlation R2 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 file (result.csv)

Model Correlation R2 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

The output file contains columns of input file along with two additional columns having Topsis_score and Rank.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

Topsis-Pramit-101903198-1.0.1.tar.gz (4.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

Topsis_Pramit_101903198-1.0.1-py3-none-any.whl (5.4 kB view details)

Uploaded Python 3

File details

Details for the file Topsis-Pramit-101903198-1.0.1.tar.gz.

File metadata

  • Download URL: Topsis-Pramit-101903198-1.0.1.tar.gz
  • Upload date:
  • Size: 4.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.4

File hashes

Hashes for Topsis-Pramit-101903198-1.0.1.tar.gz
Algorithm Hash digest
SHA256 1e69643c22e1da6b7ed4f10c8d403ff86017b8fb2ff4c1d387d1aa0aff3c055a
MD5 526b48bbd047a186a6a99cf837db6b0c
BLAKE2b-256 f1341f3d46b323e5b6a6c36a6affa576d00c7045ba70ec8aa79f288e88688955

See more details on using hashes here.

File details

Details for the file Topsis_Pramit_101903198-1.0.1-py3-none-any.whl.

File metadata

File hashes

Hashes for Topsis_Pramit_101903198-1.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 4590073a43943a52b47c856c8f64494d108c3d917c9095172f2356db01d28e7d
MD5 e63624bfed56637c03d0b78d46ae40d7
BLAKE2b-256 bf977b309d619800129fd00c38b360c6846f3d41752c0c2140e16bdd62c74460

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page