semvec/pypi-packages huggingface dataset:
TOPSIS-Saumyaa-101803609 0.0.9
topsis package
License: MIT
Requires Python: >=3.6

# TOPSIS-Python

**Subject : UCS538**
Assignment 6


Submitted By: **Saumyaa Mathur 101803609**

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## What is TOPSIS

The Technique for Order of Preference by Similarity to Ideal Solution is a multi-criteria decision analysis method.It 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

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## How to use this package:

TOPSIS-Saumyaa-101803609 can be run as in the following example:

Usages:
python topsis \<InputDataFile\> \<Weights\> \<Impacts\> \<ResultFileName\>
  <br>
Example:
python topsis inputfile.csv “1,1,1,2” “+,+,-,+” result.csv

### In Command Prompt
```
>> topsis_cmd data.csv "1,1,1,1" "+,+,-,+" result.csv
```
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### In Python IDLE:
from topsis_py.topsis import topsis
<br>
topsis('data.csv','1,1,2,2','+,+,-,+','result.csv')

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## Sample dataset (.csv)

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

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## Output file (.csv)

Model | Correlation | R<sup>2</sup> | RMSE | Accuracy | Topsis score | Rank
------------ | ------------- | ------------ | ------------- | ------------ | ------------- | -----------
M1 |	0.79 | 0.62	| 1.25 | 60.89 | 0.77221 | 2 
M2 |  0.66 | 0.44	| 2.89 | 63.07 | 0.225599 | 5
M3 |	0.56 | 0.31	| 1.57 | 62.87 | 0.438897| 4
M4 |	0.82 | 0.67	| 2.68 | 70.19 | 0.523878 | 3
M5 |	0.75 | 0.56	| 1.3	 | 80.39 | 0.811389 | 1

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TOPSIS-Shivam-101803315 1.0.1
Topsis score calculator
License: MIT
Keywords: topsis,thapar,rank,topsis score

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.

This is a package to find topsis score and rank of a dataframe with only numerical values.

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

Command Line Usage :

>>python topsis.py "input.csv" "1,1,1,2" "+,+,+,-" "out.csv"
topsis-jatin 0.0.1
topsis score and rank calculator
License: MIT
Keywords: topsis

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. More

How to use this package:
TOPSIS-Jatin-101866020 can be run as in the following example:

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