Metadata-Version: 2.1
Name: TOPSIS-SimranKaur-101803192
Version: 1.0.1
Summary: Python Package for TOPSIS
Home-page: UNKNOWN
Author: Simran Kaur
Author-email: skaur4_be18@thapar.edu
License: MIT
Description: # TOPSIS
        
        Code by: Simran Kaur 
        
        <hr style = "border:2px solid gray"> </hr>
        ## What is TOPSIS
        
        TOPSIS stands for â€˜The Technique for Order of Preference by Similarity to the Ideal Solutionâ€™ is a multi-criteria decision analysis(MCDA) method. It is a method of compensatory aggregation that compares a set of alternatives by identifying weights for each criterion, normalising scores for each criterion and calculating the geometric distance between each alternative and the ideal alternative, which is the best score in each criterion.
        
        
        ## How to run
        
        #### Before running, make sure you have pandas installed on your system
        
        Open Terminal and input the following commands
        
        
        >> pip install Topsis-SimranKaur-101803192
        
        
        
        >> python
        >>>from topsis.topsis1 import topsis
        >>>topsis("input.csv","1,2,1,2","+,+,-,+","output.csv")
        
        ## Sample Input
        
        This input was used to test the module
        
        <table><thead><tr><th>Model</th><th>Corr</th><th>Rseq</th><th>RMSE</th><th>Accuracy</th></tr></thead><tbody><tr><td>M1</td><td>0.79</td><td>0.62</td><td>1.25</td><td>60.89</td></tr><tr><td>M2</td><td>0.66</td><td>0.44</td><td>2.89</td><td>63.07</td></tr><tr><td>M3</td><td>0.56</td><td>0.31</td><td>1.57</td><td>62.87</td></tr><tr><td>M4</td><td>0.82</td><td>0.67</td><td>2.68</td><td>70.19</td></tr><tr><td>M5</td><td>0.75</td><td>0.56</td><td>1.3</td><td>80.39</td></tr></tbody></table>
        
        ## Output 
        
        
        <table><thead><tr><th>Model</th><th align="right">Corr</th><th align="center">Rseq</th><th>RMSE</th><th>Accuracy</th><th>Topsis Score</th><th>Rank</th></tr></thead><tbody><tr><td>M1</td><td align="right">0.79</td><td align="center">0.62</td><td>1.25</td><td>60.89</td><td>0.639133</td><td>2.0</td></tr><tr><td>M2</td><td align="right">0.66</td><td align="center">0.44</td><td>2.89</td><td>63.07</td><td>0.212592</td><td>5.0</td></tr><tr><td>M3</td><td align="right">0.56</td><td align="center">0.31</td><td>1.57</td><td>62.87</td><td>0.407846</td><td>4.0</td></tr><tr><td>M4</td><td align="right">0.82</td><td align="center">0.67</td><td>2.68</td><td>70.19</td><td>0.519153</td><td>3.0</td></tr><tr><td>M5</td><td align="right">0.75</td><td align="center">0.56</td><td>1.3</td><td>80.39</td><td>0.828267</td><td>1.0</td></tr></tbody></table>
        
        
        ## License
        
        Â© 2020 Simran Kaur
        
        This repository is licensed under the MIT license. See LICENSE for details.
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
