Package for Multiple-criteria decision-making using TOPSIS.Requires input file,weights and impacts. Returns dataframe with score and rank of every label.This package can help improve decision-making.
Project description
Topsis
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.
Purpose
Package for Multiple-criteria decision-making using TOPSIS. Requires input file,weights and impacts. Returns a data frame which has score and rank of every label. This package can help improve decision-making.
Use the package manager pip to install Topsis-Mitul-101803084.
pip install Topsis-Mitul-101803084
Usage
from TOPSIS_Mitul_101803084 import Topsis_rank
Topsis_rank("input.csv","1,1,1,2","+,+,+,-")
# Outputs a dataframe with score and rank columns
from TOPSIS_Mitul_101803084 import Topsis_rank
# if output file name is provided,output file is saved in your current directory
Topsis_rank("input.csv","1,1,1,2","+,+,+,-","output.csv")
# Dataframe named output.csv will be saved in your current directory.
Things to take care
- Weights and Impacts provided as arguments should be separated by comma's and equal to number of numerical columns.
- Categorical columns are not supported yet. They should be dropped or feature engineered into numerical columns using techniques like One Hot encoding etc.
- First column should be label column.
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