semvec/pypi-packages huggingface dataset:
TOPSIS-Pranshu-101803102 0.0.1
This package allows you to run The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) on your dataset for Multiple Attribute Decision Making(MADM)'
License: MIT

# topsis_pckg
It is a Python package to find out the best value among the different data using the mathematical calculations.
## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install this package.

```bash
pip install TOPSIS_Pranshu_101803102
```

## About
TOPSIS is an acronym that stands for 'Technique of Order Preference Similarity to the Ideal Solution' and is a pretty straightforward MCDA 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

To get started quickly, just use the following:

```bash
from topis_pckg.topsis import topsis
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.

## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.


## License
[MIT](https://choosealicense.com/licenses/mit/)
TOPSIS-Mehul-101816021 1.0
A Python package to find TOPSIS for multi-criteria decision analysis method
License: MIT
Keywords: topsis,UCS538,TIET

Topsis Value Calculator

CalcTopsis is a Python package implementing Topsis method sed for multi-criteria decision analysis.
Topsis stands for Technique for Order of Preference by Similarity to Ideal Solution

Just provide your input attributes and it will give you the results


## Installation

$ pip install TOPSIS-Mehul-101816021==1.0

In the commandline, you can write as -
    $ python <package_name> <path to input_data_file_name> <weights as strings> <impacts as strings> <result_file_name>

E.g for input data file as data.csv, command will be like
    $ python topsis.py data.csv "1,1,1,1" "+,+,-,+" output.csv

This will print all the output attribute values along with the Rank column, in a tabular format

License -> MIT

Change Log
==========

1.0 (12/11/2020)
------------------
- First Release
TOPSIS-Rahet-101803173 1.1
A Python package implementing TOPSIS technique.
License: MIT

# TOPSIS-Python

## What is 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.


## How to use this package:



TOPSIS-Rahet-101803173 can be run as in the following example:

### In command prompt:

```bash
>> TOPSIS data.csv "1,1,2,1" "+,-,+,-" result.csv
```




## Sample Dataset

```python



Model	Correlation	  R2	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

```

## Output

```python
Model   Score    Rank
-----  --------  ----
  1    0.77221     2
  2    0.225599    5
  3    0.438897    4
  4    0.523878    3
  5    0.811389    1

```
zmazino 0.0.6
Modern utils library
License: MIT
Requires Python: >=3.5, <4
Keywords: utils

### Logger

```python
if __name__ == "__main__":
    logger = Logger("logger")
    logger.debug("debug")
    logger.info("info")
    logger.warning("warning")
    logger.error("error")
```

### Author

[KhoiDD](https://github.com/mazino2d)