Topsis-Prateek-101916078 1.0.1

Topsis in python that take input csv file and outputs csv file

TOPSIS. Submitted By: Prateek Rai.

Type: Package.

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

Version: 1.0.0.

Author: Prateek Rai.

Maintainer: Prateek Rai [e-mail].

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

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-Prateek-101916078

In Command Prompt : python 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. The file should be put in the command line as the location of the file.

| Fund Name | P1 | P2 | P3 | P4 | P5 | | M1 | 0.73 | 0.53 | 3.4 | 46 | 12.67 | | M2 | 0.72 | 0.52 | 4.1 | 35 | 10.09 | | M3 | 0.83 | 0.69 | 3.1 | 48.6 | 13.31 | | M4 | 0.85 | 0.72 | 4.3 | 59.8 | 16.42 | | M5 | 0.93 | 0.86 | 4.9 | 64.3 | 17.75 | | M6 | 0.73 | 0.53 | 4.7 | 44.1 | 12.52 | | M7 | 0.88 | 0.77 | 6.3 | 41.7 | 12.41 | | M8 | 0.8 | 0.64 | 4.8 | 67.4 | 18.41 |

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)

| Fund Name | P1 | P2 | P3 | P4 | P5 | Topsis Score | Rank | | M1 | 0.73 | 0.53 | 3.4 | 46 | 12.67 | 0.5443557844202768 | 4 | | M2 | 0.72 | 0.52 | 4.1 | 35 | 10.09 | 0.4256480475457405 | 6 | | M3 | 0.83 | 0.69 | 3.1 | 48.6 | 13.31 | 0.7477966268745603 | 1 | | M4 | 0.85 | 0.72 | 4.3 | 59.8 | 16.42 | 0.6228391928555446 | 3 | | M5 | 0.93 | 0.86 | 4.9 | 64.3 | 17.75 | 0.6268025462066721 | 2 | | M6 | 0.73 | 0.53 | 4.7 | 44.1 | 12.52 | 0.3278090845190438 | 7 | | M7 | 0.88 | 0.77 | 6.3 | 41.7 | 12.41 | 0.3182486586359413 | 8 | | M8 | 0.8 | 0.64 | 4.8 | 67.4 | 18.41 | 0.47120452726540807 | 5 |

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