topsis-kjindal-101703299 1.0.1

A python package to identify the best model out of various mobile phone models using TOPSIS

Ranking System Using Topsis

Project 1 : UCS633

Submitted By: Kunal Jindal 101703299

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pypi: https://pypi.org/project/topsis-kjindal-101703299/

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Installation

Use the package manager pip to install topsis-kjindal-101703299.

pip install topsis-kjindal-101703299

How to use this package:

topsis-kjindal-101703299 can be run as shown 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(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.