semvec/pypi-packages huggingface dataset:
Topsis-Himanshu-102017110 1.0.1
A Python package implementing TOPSIS technique.
License: MIT

# TOPSIS-Python

**Project 1 : UCS654**


Submitted By: **HIMANSHU NAGPAL 102017110**


## What is TOPSIS

**T**echnique for **O**rder **P**reference by **S**imilarity 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-HIMANSHU-102017110  can be run as in the following example:



### In Command Prompt
```
>> topsis 102017110-data.csv "1,1,1,1,1" "+,+,-,+,+" 102017110-result.csv
```


## 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

Weights (`w`) is not already normalised will be normalised later in the code.

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-gurleen-102003138 0.3
This package is implementation of Multiple-criteria decision making using Topsis Algorithm
License: MIT
Keywords: TOPSIS,MULTIPLE CRITERIA DECISION MAKING,MCDM

# Topsis
## By Gurleen Kaur, 102003138
This package can be used for implementation of Multiple criteria decision making using Topsis Algorithm. This is a python library for dealing with Multi-Criteria Decision Making (MCDM) problems by using techniques for order of preference by similarity to ideal solution (TOPSIS).
## Installation
```sh
pip install topsis-gurleen-102003138
```
## How to use
This package will accept four arguments during file execution:
1. dataset.csv (file path which contains the dataset)
2. string of weights separated by commas(,)
3. string of impacts (+/-) separated by commas(,)
4. result.csv (file path where the result needs to be stored)

## Pre-requirements

install pandas and math libraries before installing this package
```sh
pip install pandas
pip install math
```
You can install this package using following command
```sh
pip install topsis_gurleen_102003138
```


## License
Â© 2023 Gurleen Kaur
This repository is licensed under the MIT license. See LICENSE for details.