Topsis-Sudhit-102017137 0.1

This is a topsis package of version 0.1

Topsis_Sudhit_102017137

TOPSIS

Submitted By: Sudhit Soni - 102017137.

Type: Package.

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

Version: 1.0.0.

Date: 2022-01-22.

Author: Sudhit Soni.

Maintainer: Sudhit Soni [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-Sudhit-102017137

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.

Fund Name P1 P2 P3 P4 P5 M1 0.63 0.4 6.4 64.4 17.96 M2 0.85 0.72 3.2 69.6 18.59 M3 0.94 0.88 4 31 9.21 M4 0.68 0.46 5.6 32.4 9.79 M5 0.69 0.48 5.5 38.5 11.29 M6 0.7 0.49 5.7 34.1 10.25 M7 0.93 0.86 6.6 60.5 17.22 M8 0.62 0.38 3.6 64.5 17.28

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 (out.csv)

Fund Name P1 P2 P3 P4 P5 Topsis Score Rank M1 0.77 0.59 3.4 64.7 17.37 0.590504815 3 M2 0.76 0.58 6.1 51.5 14.74 0.402338394 6 M3 0.61 0.37 4.2 53.9 14.77 0.406862418 5 M4 0.7 0.49 7 34.3 10.62 0.320024918 8 M5 0.94 0.88 4.4 63.5 17.43 0.699428496 2 M6 0.93 0.86 6.5 57 16.32 0.568238573 4 M7 0.91 0.83 3.2 59.6 16.14 0.757501032 1 M8 0.67 0.45 7 64.3 18.11 0.327902786 7

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