This is a Python library for handling problems related to Multiple Criteria Decision Making(MCDM)
Project description
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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Source Distribution
Hashes for TOPSIS-Ankita-102017120-1.0.0.2.tar.gz
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