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Python library for handling problems related to Multiple Criteria Decision Making (MCDM)

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Topsis-102017120-Ankita

Topsis-Ankita-102017120 is a Python library for handling problems related to Multiple Criteria Decision Making(MCDM)

Topsis-Ankita-102017120 is a Python library for handling problems related to Multiple Criteria Decision Making(MCDM) where there are more than one features to consider while arriving at a situation.By using Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS),we can efficient conclusions to help us arrive at the decision

Installation

Use the package manager pip to install Topsis-Ankita-102017120

Syntax

topsis <InputDataFile> <Weights> <Impacts> <ResultFileName>
Example:
topsis inputfile.csv “1,1,1,2” “+,+,-,+” result.csv
or 
topsis inputfile.csv 1,1,1,2 +,+,-,+ result.csv

Example

Sample input data

Model Corr Rseq RMSE Accuracy
M1 0.79 0.62 1.25 60.89
M2 0.66 0.44 2.89 63.07
M3 0.56 0.31 1.57 62.87
M4 0.82 0.67 2.68 70.19
M5 0.75 0.56 1.3 80.39

Sample Output Data

Model Corr Rseq RMSE Accuracy Topsis Score Rank
M1 0.79 0.62 1.25 60.89 0.7731301458119156 2
M2 0.66 0.44 2.89 63.07 0.22667595732024362 5
M3 0.56 0.31 1.57 62.87 0.4389494866695491 4
M4 0.82 0.67 2.68 70.19 0.5237626971836845 3
M5 0.75 0.56 1.3 80.39 0.8128626132980138 1

Please Note

1.Enter the path for your input csv file
2.Enter the weights vector with each weight separated by commas
3.Enter the impact vector with each impact separated by commas
4.Enter the name of csv file in which you want to store output dataframe.
This file will be created in the current wokring directory

License

MIT

Free Software, Hell Yeah!

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Python library for handling problems related to Multiple Criteria Decision Making (MCDM)

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