A python package to identify the best model out of various mobile phone models using TOPSIS
Project description
Ranking System Using Topsis
Project 1 : UCS633
Submitted By: Kunal Jindal 101703299
pypi: https://pypi.org/project/topsis-kjindal-101703299/
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.
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