Skip to main content

A Python package implementing TOPSIS for MCDM

Project description

Ekaspreet-topsis-102017078

Topsis in Python

Author: Ekaspreet 102017078
Maintainer: Ekaspreet ekaspreet0209@gmail.com.

TOPSIS: It is a for Multiple Criteria Decision Making,A Technique for Order Preference by Similarity to Ideal
More details at wikipedia.


In Command Prompt

>> topsis data.csv "1,1,1,1" "+,+,-,+" result.csv

Input file (data.csv)

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

Weights (weights) is not already normalised will be normalised later in the code.

Information of positive(+) or negative(-) impact criteria should be provided in impacts.


Output file (result.csv)

Model Correlation R2 RMSE Accuracy 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 **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

Ekaspreet-topsis-102017078-1.0.1.tar.gz (4.4 kB view hashes)

Uploaded Source

Built Distribution

Supported by

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