semvec/pypi-packages huggingface dataset:
Topsis-Bhagesh-101903540 1.0.0
It performs topsis for any model
License: MIT

# Topsis-Bhaegesh-10193540

This package is implementation of topsis technique of multi-criteria decision analysis. This package will accept three parameters as input:


1. .csv file which contains the models and parameters
2. string of weights separated by commas(,)
3. string of requirements (+/-) separated by commas(,) 

It performs the topsis, calculate the Performance
Score and Rank according to the inputs and store them in the output file.
This program must be run through command line only.
### What is TOPSIS
The Technique for Order of Preference by Similarity to Ideal Solution
(TOPSIS) is a multi-criteria decision analysis method.
TOPSIS is based on the concept that the chosen alternative should have the shortest geometric distance from the positive ideal solution (PIS)
and the longest geometric distance from the negative ideal solution (NIS).
### Installation 
To install this module write the following line in the command prompt.

```pip install Topsis-Bhagesh-101903540```
### How to use this package
Topsis-Shubham-101903131 1.1.3
A Python package implementing TOPSIS technique.
License: MIT

# TOPSIS-Python

Submitted By: **Shubham 101903131**

---

## 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-Shubham-101903131 can be run as in the following example:

### In Command Prompt

```
>> topsis data.csv "1,1,1,1" "+,+,-,+" output_file.csv
```

<br>

### In Python IDLE:

```
>>> import pandas as pd
>>> from topsis_py.topsis import topsis
>>> dataset = pd.read_csv('data.csv').values
>>> d = dataset[:,1:]
>>> w = [1,1,1,1]
>>> im = ["+" , "+" , "-" , "+" ]
>>> topsis(d,w,im,"output_file.csv")
```

<br>
<br>

The rankings are displayed in the form of a table using a package 'tabulate', with the 1st rank offering us the best decision, and last rank offering the worst decision making, according to TOPSIS method.
topsis-dilmanpreet-101903506 1.2
It's a package that calcuates Topsis score and ranks accordingly
License: MIT

# topsis_dilmanpreet_101903506

# TOPSIS

Submitted By: **Dilmanpreet Singh**.<br>
Roll Number: **101903506**.<br>
Type: **Package**.<br>
Title: **TOPSIS for multiple-criteria decision making (MCDM)**.<br>
Version: **1.0**.<br>
Date: **2022-2-24**.

Description: **Evaluation of alternatives based on multiple criteria using TOPSIS method.**.

---

## What is TOPSIS?

TOPSIS or **T**echnique for **O**rder **P**reference by **S**imilarity to **I**deal **S**olution is a method of compensatory aggregation that compares a set of alternatives by identifying weights for each criterion, normalising scores for each criterion and calculating the geometric distance between each alternative and the ideal alternative, which is the best score in each criterion.

<br>

## How to install this package:

```
>> pip install topsis-dilmanpreet-101903506
```

### In Command Prompt

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


## Process

First we create an evaluation matrix which consists of m alternatives and n criterias, with the intersection of each alternative and criteria. Then we move to the preprocessing phase. We then normalize the matrix using norm. Weighted normalised decision matrix is then calculated. We then determine the best and worst alternatives. After that, we calculate the euclidean distance between the target alternative and the worst condition. Finally, the similarity to the worst condition checked and the alternatives are ranked according to the final performance scores, awarding lower rank to higher performance score.


## Input file (data.csv)

![input](https://user-images.githubusercontent.com/83512136/155395288-72ef06f5-d407-4dc5-ae3f-954110a36fed.JPG)


<br>

## Output -- (result.csv)

![result](https://user-images.githubusercontent.com/83512136/155395048-9ae09f09-47b6-4ad3-9e7d-46010384bbb7.JPG)


<br>
The output file contains columns of input file along with two additional columns for Topsis_score and Rank
Topsis-Yoshna-101903502 1.0.0
A Python package implementing TOPSIS technique.
License: MIT

# TOPSIS-Python

Submitted By: _Yoshna Marwaha_

---

## 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-Yoshna-101903502 can be run as in the following example:

### In Command Prompt

> > topsis data.csv "1,1,1,1" "+,+,-,+" output.csv

<br>

### In Python IDLE:

> > > import pandas as pd
> > > from topsis_py.topsis import topsis
> > > dataset = pd.read_csv('data.csv').values
> > > d = dataset[:,1:]
> > > w = [1,1,1,1]
> > > im = ["+" , "+" , "-" , "+" ]
> > > topsis(d,w,im,output.csv)

<br>
<br>

The rankings are displayed in the form of a table using a package 'tabulate', with the 1st rank offering us the best decision, and last rank offering the worst decision making, according to TOPSIS method.
TOPSIS-ANKITAPURI-101903766 1.0
It's a package that calcuates Topsis score and ranks accordingly
License: MIT

# TOPSIS
 TOPSIS, known as Technique for Order of Preference by Similarity to Ideal Solution, is a multi-criteria decision analysis method. it compares a set of alternatives based on a pre-specified criterion. The method is used in the business across various industries, every time we need to make an analytical decision based on collected data.
topsis-Ankita-cal 1.0
It's a package that calcuates Topsis score and ranks accordingly
License: MIT

# TOPSIS
 TOPSIS, known as Technique for Order of Preference by Similarity to Ideal Solution, is a multi-criteria decision analysis method. it compares a set of alternatives based on a pre-specified criterion. The method is used in the business across various industries, every time we need to make an analytical decision based on collected data.