semvec/pypi-packages huggingface dataset:
TOPSIS-GARVIT-101803122 0.0.1
Find the Topsis Score Easily

# TOPSIS-GARVIT-101803122

TOPSIS-GARVIT-101803122 is a package that will provide feature to do multi-criteria decision making in choosing the best models among the data provided.

  - It will provide with the TOPSIS Score.
  - It will do Ranking of Models on the basis of the given data.

# TOPSIS:

Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) originated in the 1980s as a multi-criteria decision making method. TOPSIS chooses the alternative of shortest Euclidean distance from the ideal solution, and greatest distance from the negative-ideal solution. 


### Installation
TOPSIS-GARVIT-101803122 requires [Python](https://www.python.org/) v2.7+ to run.

Install the package using pip as follows :

```sh
$ pip install TOPSI-GARVIT-101803122
```

### HOW TO USE THIS PACKAGE

TOPSIS-GARVIT-10803122 can be run as in the following examples:




### Sample Dataset
The decision matrix (a) will be extracted from the csv file as the pandas dataframe which will contain each row representing a Model alternative, and each column representing a criterion like Accuracy, RSeq, Root Mean Squared Error, Correlation, and many more.

| Model | Correlation | 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

Weights (w) is not already normalised will be normalised later in the code.
Information of impacts positive(+) or negative(-) impact criteria should be provided in (im).



License
----

MIT License

Copyright (c) 2020 Garvit Garvit

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
TOPSIS-PANKAJ-101803352 0.4
Multiple Criteria Decision Making using Topsis

ï»¿
Project Description
-------------
TOPSIS implementation for Multi Criteria Decision Making(MCDM)

The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is a multi-criteria decision analysis method, which is based on the concept that the chosen alternative should have the shortest geometric distance from the positive ideal solution (PIS)[4] and the longest geometric distance from the negative ideal solution (NIS).

The package (TOPSIS_PANKAJ_10180332) contains the python script topsis.py and it further contains the function topsis_score which has to given 4 parameters -

1. Name of input .csv file.
2. Weights of all the attributes in the form of list.
3. Impact of all the parameters(either '+' or '-') in form of list.
4. Name of output .csv file.

Note - All the column entries should be numeric only.

Example code :

import TOPSIS_PANKAJ_101803352.topsis as top

top.topsis_score('inputFile.csv', [1,1,1,1], ['+','+','-','+',],'outputFile.csv')