Metadata-Version: 2.1
Name: TOPSIS-Shruti-101803512
Version: 1
Summary: A Python pip package to apply topsis approach to rank the entries in a dataset
Home-page: UNKNOWN
Author: Shruti Bansal
License: MIT
Description: # TOPSIS\_Shruti\_101803512
        
        ## What is TOPSIS ?
        The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is a multi-criteria decision analysis method
        
        ### How to use the package
        TOPSIS_Shruti_101803512 package should be used as:
        ### In command prompt
        
        >\>> pip install TOPSIS_Shruti_101803512
        
        >\>> python 
        >\>> import TOPSIS_Shruti_101803512 as t
        >\>> t.topsis_evaluation(<InputDataFile>,<Weights>,<Impacts>,<ResultFileName>)
        >\>> t.topsis_evaluation("data.csv","1,1,1,2","+,+,-,+","result.csv")
        
        ### Some instructions:
        > â€¢ Input file must contain three or more columns.
        > â€¢ From 2nd to last columns must contain numeric values only (Handling of non-numeric values)
        > â€¢ Number of weights, number of impacts and number of columns (from 2nd to last columns) must
        be same.
        > â€¢ Impacts must be either +ve or -ve.
        > â€¢ Impacts and weights must be separated by â€˜,â€™ (comma).
        
        ## Example:
        The dataset upon which topsis is to be performed is taken as folows. It will be in the form of a csv file.
        #### Sample Input
        
        | 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    |
        
        The following output with performance score and rank will be produced in a result(csv file) file and printed as output. 1st rank offering us the best decision, and last rank offering the worst decision making, according to TOPSIS method.
        #### OUTPUT
        
        | Model | Corr | Rseq | RMSE | Accuracy | Topsis Score        | Rank |
        |-------|------|------|------|----------|---------------------|------|
        | M1    | 0.79 | 0.62 | 1.25 | 60.89    | 0.6391330141342587  | 2    |
        | M2    | 0.66 | 0.44 | 2.89 | 63.07    | 0.21259182969277918 | 5    |
        | M3    | 0.56 | 0.31 | 1.57 | 62.87    | 0.4078456776130516  | 4    |
        | M4    | 0.82 | 0.67 | 2.68 | 70.19    | 0.5191532395007472  | 3    |
        | M5    | 0.75 | 0.56 | 1.3  | 80.39    | 0.8282665851935813  | 1    |
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
