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Ranking System Using Topsis

Project 1 : UCS633

Submitted By: Rajat Gupta 101703427

Installation

Use the package manager pip to install Ranking system.

pip install topsis-RajatGupta-101703427

How to use this package:

topsis-RajatGupta-101703427 can be run as done below:

In Command Prompt

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

In Python IDLE:

>>> import pandas as pd
>>> 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.

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 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.

Release files for topsis-RajatGupta-101703427 1.0.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

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Source distribution for topsis-RajatGupta-101703427 1.0.0
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Table of built distributions (wheels) for topsis-RajatGupta-101703427 1.0.0
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topsis_RajatGupta_101703427-1.0.0-py3-none-any.whl Python 3 none any Details

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