Metadata-Version: 2.1
Name: Topsis-Lovish-101803496
Version: 1.2.3
Summary: Implements Topsis
Home-page: UNKNOWN
Author: Lovish Gupta
Author-email: lovish.gupta.121@gmail.com
License: MIT
Description: # TOPSIS
        
        Code by: Lovish Gupta
        
        <hr style = "border:2px solid gray"> </hr>
        
        ## What is TOPSIS
        
        TOPSIS is an acronym that stands for 'Technique of Order Preference Similarity to the Ideal Solution' and is a pretty straightforward MCDA(Multi-Criteria Decision Analysis) method. As the name implies, the method is based on finding an ideal and an anti-ideal solution and comparing the distance of each one of the alternatives to those.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 Use This Package
        
        #### Before running, make sure you have pandas installed on your system
        
        Open Command Prompt and input the following commands
        
        
        >> pip install Topsis-Lovish-101803496
        
        
        
        >> python
        >>>from topsis.topsispac import topsis
        >>>topsis("data.csv","1,1,1,2","+,+,-,+","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 Lovish Gupta
        
        This repository is licensed under the MIT license. See LICENSE for details.
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/markdown
