Ranking System Using Topsis

Project 1 : UCS633

Submitted By: Pritpal Singh Pruthi 101883058

pypi: https://pypi.org/project/topsis-ppruthi-101883058/

Installation

Use the package manager pip to install foobar.

pip install topsis-ppruthi-101883058

How to use this package:

topsis-ppruthi-101883058 can be run as done below:

In Command Prompt

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

In Python IDLE:

>>> import pandas as pd
>>> from topsis_python.topsis import topsis
>>> data = pd.read_csv('data.csv').values
>>> data = data[:,1:]
>>> w = [1,1,1,1]
>>> impacts = ["+" , "+" , "-" , "+" ]
>>> topsis.topsis(data,w,impacts)

Sample dataset

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.

Weights list is not already normalised will be normalised later in the code.

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

Output

Model   Score    Rank
-----  --------  ----
  1    0.77221     2
  2    0.225599    5
  3    0.438897    4
  4    0.523878    3
  5    0.811389    1

The rankings are displayed in the form of a table using a package 'tabulate', with the 1st rank offering us the best decision, and last rank offering the worst decision making, according to TOPSIS method.

License

MIT