Metadata-Version: 2.1
Name: TOPSIS_Ansh_101803295
Version: 1.0.1
Summary: The Technique for Order of Preference by Similarity to the Ideal Solution
Home-page: https://github.com/anshgarg7/TOPSIS-Ansh-101803295
Author: Ansh Garg
Author-email: anshgarg7@gmail.com
License: UNKNOWN
Description: # TOPSIS
        
        Code by: Ansh Garg
        
        <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-Ansh-101803295
        
        To get started quickly, just use the following:
        
        >> from TOPSIS_Ansh_101803295.topsis import topsis <br>
        >> topsis('inputfilename','Weights','Impacts','Outputfilename')
        
        make ensure the weights and impacts should be in ""
        
        eg: "1,1,1,1" and "+,-,+,-"
        
        ## Pre-requisite
        The data should be enclosed in the csv file. There must be more than 2 columns
        
        
        ## Result
        the output(outputfilename)  is saved in the project folder with extra 2 columns with topsis score and rank.
        
        
        ## 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 Ansh Garg
        
        This repository is licensed under the MIT license. See LICENSE for details.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
