Topsis-Shikhar-101917064 1.2.6

A Python package implementing TOPSIS technique.

TOPSIS-Python

Submitted By: Shikhar 101917064

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What is TOPSIS

Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) originated in the 1980s as a multi-criteria decision making method. TOPSIS chooses the alternative of shortest Euclidean distance from the ideal solution, and greatest distance from the negative-ideal solution.

How to use this package:

Install it by using command : pip install Topsis_Shikhar_101917064 After installing, Topsis_Shikhar_101917064 can be run as shown in the following example:

In Command Prompt

>> python
>> import pandas as pd
>> df = pd.read_csv("data.csv")
>> import Topsis_Shikhar_101917064
>> Topsis_Shikhar_101917064.topsis(df,"1,1,1,1","+,-,+,-") 

In Python IDLE:

>>> import pandas as pd
>>> from Topsis_Shikhar_101917064 import topsis
>>> df = pd.read_csv("data.csv")
>>> weight = "1,1,1,1"
>>> impact = "+,-,+,-"
>>> topsis(df,weight,impact)

Sample dataset

The decision matrix (a) 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

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

Output

Model   Score    Rank
-----  --------  ----
  1    0.772      2
  2    0.225      5
  3    0.438      4
  4    0.523      3
  5    0.811      1

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