Topsis-Yash-101803617 0.0.4

A Python package implementing TOPSIS technique.

TOPSIS

Submitted By: Yash Shukla 101803617

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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 install this package:

>> pip install Topsis_Yash_101803617

In Command Prompt

>> python

>> import Topsis_Yash_101803617
>> Topsis_Yash_101803617.topsis("data.csv","1,1,1,1","+,+,-,+","result.csv")

You shall recieve output as a .csv file in your current working Directory. (The input file should be present in the current working directory.)

Input file (data.csv)

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 (weights) 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 file (result.csv)

Model	Correlation	R2	RMSE	Accuracy	Topsis_score	Rank
M1	0.79	0.62	1.25	60.89	0.7722	2
M2	0.66	0.44	2.89	63.07	0.2255	5
M3	0.56	0.31	1.57	62.87	0.4388	4
M4	0.82	0.67	2.68	70.19	0.5238	3
M5	0.75	0.56	1.3	80.39	0.8113	1

The output file contains columns of input file along with two additional columns having Topsis_score and Rank