Topsis-Sarisha-102003445 0.7

This is a topsis package of version 0.7

Topsis_Sarisha_102003445

TOPSIS

Submitted By: Sarisha Aggarwal - 102003445.

Type: Package.

Title: TOPSIS method for multiple-criteria decision making (MCDM).

Version: 1.0.0.

Date: 2023-01-23.

Author: Sarisha Aggarwal.

Maintainer: Sarisha Aggarwal [e-mail].

Description: Evaluation of alternatives based on multiple criteria using TOPSIS method..

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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-Sarisha-102003445

In Command Prompt

topsis data.csv "1,1,1,1,1" "+,+,+,+,+" result.csv

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	P1	P2	P3	P4	P5
M1	0.7	0.5	7	37	11.3
M2	0.8	0.6	7	46	13.4
M3	0.7	0.5	7	48	14
M4	0.9	0.8	7	44	13.2
M5	0.9	0.9	5	37	11.1
M6	0.9	0.6	3	67	18
M7	0.9	0.5	7	39	11.8
M8	0.9	0.9	5	46	13.2

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	P1	P2	P3	P4	P5	Topsis Score	Rank
M1	0.7	0.5	7	37	11.3	0.28016	5
M2	0.8	0.6	7	46	13.4	0.8292	1
M3	0.7	0.5	7	48	14	0.17536	8
M4	0.9	0.8	7	44	13.2	0.25	7
M5	0.9	0.9	5	37	11.1	0.56483	3
M6	0.9	0.6	3	67	18	0.27313	6
M7	0.9	0.5	7	39	11.8	0.55075	4
M8	0.9	0.9	5	46	13.2	0.65029	2

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