semvec/pypi-packages huggingface dataset:
mixturelib 0.4.0
mixture lib, python package
License: MIT

###########
Mixture Lib
###########

|test| |codecov| |docs| |readthedocs| |pypi| 

.. |test| image:: https://github.com/andriygav/MixtureLib/workflows/test/badge.svg
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.. |codecov| image:: https://img.shields.io/codecov/c/github/andriygav/mixturelib/master
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    :alt: Test coverage

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    :target: https://andriygav.github.io/MixtureLib/
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Basic information
=================

Implementation code for a mixture of models. The `source code <https://github.com/andriygav/MixtureLib/tree/master/src>`_ for the problem of the mixture of models and the task of the mixture of experts is presented.

All methods were implemented based on ``pytorch`` for simple parallelization by using ``cuda``.

All information about this project can be found in the `documentation <https://andriygav.github.io/MixtureLib/>`_.

Requirements and Installation
=============================
A simple instruction of installation using pip is provided near the `source code <https://github.com/andriygav/MixtureLib/tree/master/src>`_.

More information about installation can be found in documentation `installation <https://andriygav.github.io/MixtureLib/installation.html>`_ page.

Example of use
==============
A simple examples of module usage can be found in documentation `example <https://andriygav.github.io/MixtureLib/example.html>`_ page.
TOPSIS-ParthArora-101853039 1.0
This Package is for calculating the TOPSIS score and rank of a dataset and storing it in a result csv file
License: MIT
Keywords: TOPSIS,RANKING,DATAFRAME,MCDM

# TOPSIS-ParthArora-101853039
By:**Parth Arora-101853039**

### Title:Multiple Criteria Decision Making using TOPSIS

## What is TOPSIS:
TOPSIS is an acronym that stands for 'Technique of Order Preference Similarity to the Ideal Solution' and is a pretty straightforward MCDA method.
It is a multi-criteria decision analysis method, which was originally developed by Ching-Lai Hwang and Yoon in 1981 with further developments by Yoon in 1987, and Hwang, Lai and Liu in 1993.
#### How to install the TOPSIS package
```buildoutcfg
pip install TOPSIS-ParthArora-101853039
```
#### For Calculating the TOPSIS Score
```buildoutcfg
Topsis data.csv "0.25,0.25,0.25,0.25" "-,+,+,+" result.csv
```

##### Input File(Example:data.csv):
Argument used to pass the path of the input file which conatins a dataset having different fields and to perform the topsis mathematical operations
##### Weights(Example:"0.25,0.25,0.25,0.25")
The weights to assigned to the different parameters in the dataset should be passed in the argument.**It must be seperated by ','.**
##### Impacts(Example:"-,+,+,+"):
The impacts are passed to consider which parameters have a positive impact on the decision and which one have the negative impact.**Only '+' and '-' values should be passed and should be seperated with ',' only**
##### Output File(Example:result.csv):
This argument is used to pass the path of the result file where we want the rank and score to be stored
Abhishek 1.0.1
TOPSIS
License: MIT

# TOPSIS-Abhishek-101803463
TOPSIS is an acronym that stands for "Technique of Order Preference Similarity to the Ideal Solution" and is a pretty straightforward MCDA method. As the name implies, 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. 

## Installation 
'''pip install TOPSIS-Abhishek-101803463==1.0.1'''

## License
Â©  2020 Abhishek
This repository is licensed under the MIT license. 
See LICENSE for details
TOPSIS-Tanishq-101803705 0.12
A library to perform the topsis analysis and rank
License: MIT
Keywords: TOPSIS,RANK

This package is a CLI-based tool to perform TOPSIS analysis on numerical csv datasets.

It outputs a csv file with the TOPSIS results.

Usage: 

TOPSIS-Tanishq-101803705 input_file weights impacts output_file

Example:
TOPSIS-Tanishq-101803705 input.csv 1112 +-++ output.csv


This generates the output in 'output.csv' file.

Usage Requirements:

 - Input dataset must have atleast three columns.
 - First column must be Descriptor.
 - Weights and Impacts must be comma (,) separated.
TOPSIS-RATISH-101803004 1.0.0
A Python package implementing TOPSIS technique.
License: MIT

# TOPSIS


Submitted By: **Ratish 101803004**

***

## 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. 

<br>

## How to install this package:
```
>> pip install TOPSIS-RATISH-101803004
```


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