Topsis-Rishabh-102003393 1.0

# Topsis The package includes a TOPSIS class that can be used to perform the analysis. The class takes the following parameters:

Source File: Contains a decision matrix with rows as alternatives and columns as criteria Weights: A string representing the weight of each criterion Impacts: A string representing the impact of each criterion (+ for positive impact, - for negative impact)

# Algorithm : ### STEP 1 : Create an evaluation matrix consisting of m alternatives and n criteria, with the intersection of each alternative and criteria. Apply any preprocessing if required. ### STEP 2 : The matrix is then normalised using the norm.

### STEP 3 : Calculate the weighted normalised decision matrix.

### STEP 4 : Determine the worst alternative and the best alternative.

### STEP 5 : Calculate the L2-distance between the target alternative i and the worst condition.

### STEP 6 : Calculate the similarity to the worst condition.

### STEP 7 : Rank the alternatives according to final performance scores.

## To install this package : Use pip install VanshikaPackage pip install VanshikaPackage

## To run the topsis function topis <sourcefile.csv> “<weights_seperated_by_commas>” “<impact_seperated_by_commas>” <destinationfilename.csv> ## example topsis srcfile.csv “1,1,1,2” “+,+,+,-” dstfile.csv ## License

© 2023 Rishabh

This repository is licensed under the MIT license. See LICENSE for details.