semvec/pypi-packages huggingface dataset:
Topsis-Kunal-102053007 0.3
This is a topsis package of version 0.3

## Topsis_Kunal_102053007

# TOPSIS

Submitted By: Kunal Madan - 102053007.

Type: Package.

Title: *TOPSIS method for multiple-criteria decision making (MCDM)*.

Version: 1.0.0.

Date: 2022-01-22.

Author: Kunal Madan.

Maintainer: *Kunal Madan <kmadan_bemba20@thapar.edu>*.

Description: *Evaluation of alternatives based on multiple criteria using TOPSIS method.*.

---

## What is TOPSIS?

*Technique for **Order **Preference by **Similarity to **Ideal **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.

<br>

## How to install this package:


>> pip install Topsis-Kunal-102053007


### In Command Prompt


>> topsis data.csv "1,1,1,1,1" "+,+,-,+,-" result.csv


## Input file (data.csv)

The decision matrix 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 |     P1      | P2 | P3 | P4 | P5 |
| ----- | ----------- | ------------- | ---- | -------- | ---- |
| M1    | 0.66       | 0.44        | 4.9 | 32.9    | 9.73 |
| M2    | 0.65        | 0.42          | 5 | 44.5    | 12.64 |
| M3    | 0.61       | 0.37          | 3.3 | 41.1    | 11.35 |
| M4    | 0.62        | 0.38          | 6.5 | 64.1    | 17.9 |
| M5    | 0.83        | 0.69          | 6.4  | 34.4    | 10.58 |
| M6    | 0.88        | 0.77          | 6.7  | 34.8    | 10.79 |
| M7    | 0.63        | 0.4          | 4.5  | 39.1    | 11.16 |
| M8    | 0.8        | 0.64          | 4.4  | 45.7    | 12.89 |

Weights (`weights`) is not already normalised will be normalised later in the code.

Information of benefit positive(+) or negative(-) impact criteria should be provided in `impacts`.

<br>

## Output file (out.csv)

| Model |     P1      | P2 | P3 | P4 | P5 | Topsis Score | Rank |
| ----- | ----------- | ------------- | ---- | -------- | ---- |-----| ----|
| M1    | 0.66       | 0.44        | 4.9 | 32.9    | 9.73 | 0.21189353869415917 | 6
| M2    | 0.65        | 0.42          | 5 | 44.5    | 12.64 |0.3271776939542866|5
| M3    | 0.61       | 0.37          | 3.3 | 41.1    | 11.35 |0.15153299377397803|8
| M4    | 0.62        | 0.38          | 6.5 | 64.1    | 17.9 |0.5850881941527206|1
| M5    | 0.83        | 0.69          | 6.4  | 34.4    | 10.58 |0.49092824102735394|3
| M6    | 0.88        | 0.77          | 6.7  | 34.8    | 10.79 |0.5427136027309007|2
| M7    | 0.63        | 0.4          | 4.5  | 39.1    | 11.16 |0.2008035122309426|7
| M8    | 0.8        | 0.64          | 4.4  | 45.7    | 12.89 |0.48154813555267983|4

<br>
The output file contains columns of input file along with two additional columns having Topsis_scoreÂ andÂ Rank