semvec/pypi-packages huggingface dataset:
topsis-Kushagra-101917112 0.1
A Python package implementing TOPSIS technique.
License: MIT

# TOPSIS-Python

Submitted By: *Kushagra 101917112*

*

## What is TOPSIS

*Technique for **Order **Preference by **Similarity to **I*deal
*S*olution (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. More details at [wikipedia](https://en.wikipedia.org/wiki/TOPSIS).

<br>

## How to use this package:

TOPSIS-Kushagra 101917112  can be run as in the following example:


### In Command Prompt

>> topsis data.csv "1,1,1,1" "+,+,-,+"


<br>

## Sample dataset

The decision matrix (`a`) should be constructed with each row representing a Model alternative, and each column representing a criterion like Accuracy, R<sup>2</sup>, Root Mean Squared Error, Correlation, and many more.

Model | Correlation | R<sup>2</sup> | 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

Information of benefit positive(+) or negative(-) impact criteria should be provided in `I`.

<br>

## Output


Model   Score    Rank
-----  --------  ----
  1    0.77221     2
  2    0.225599    5
  3    0.438897    4
  4    0.523878    3
  5    0.811389    1

<br>
Topsis-Samridhi-101916086 1.2
Problem solving MCDM, Topsis Score and Rank generator
License: MIT
Keywords: topsis,topsis score,rank,MCDM

# TOPSIS
Technique for Order Preference by Similarity to Ideal Solution is a multi-criteria decision making method. 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. TOPSIS chooses the alternative of shortest Euclidean distance from the ideal solution, and greatest distance from the negative-ideal solution.
## Package Usage
To install the package:
pip install Topsis_Samridhi_101916086
This is a package focusing on finding the topsis score and rank of a dataframe (csv file) with only numerical values except for the first column.
## OUTPUT
The python file consists of the logic which excepts 4 parameter:
1. Input csv file
2. Weights given by user comma separted
3. Impact given by user comma separated
4. Result csv file, just to restore the naming convention.. result file will contain 2 additional columns contianing topsis_score and rank
## LICENSE
2022 Samridhi Garg