Metadata-Version: 2.1
Name: Rudraya
Version: 0.19
Summary: UNKNOWN
Author: ['Tushar Kolekar', 'Sameer Sayyad']
Author-email: tusharkolekar24@gmail.com
License: MIT
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
License-File: LICENCE
Requires-Dist: numpy
Requires-Dist: sklearn
Requires-Dist: pandas
Requires-Dist: seaborn
Requires-Dist: statsmodels

## Rudraya
This package aims to build a Machine Learning model to analyze the data using the various analytical technique. It performs Exploratory data analysis, data cleaning, and data wrangling process to select the most relevant feature that has a major contribution to the target feature. 

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install Rudraya.

```bash
pip install Rudraya
```

## Main Features
Filter Techniques:
* Missing Value
* Multicollinearity 
* Correlation 
* F_Regression
* Analysis Variance Test
* Forward Feature Selection
* Backword Feature Elimination

## Ensemble Learning
* Average Ensemble
* Weighted Average Ensemble
* Rank Average Ensemble
* Voting Ensemble
* Stack Regression

## Evaluation
* Mean Sequared Error
* Mean Absolute Error
* Mean Absolute Percentage Error
* Root Mean Square Error
* R2 score

## Time domain Feature Analysis

## Documentation
The documentation for the latest release is at

https://rudraya.readthedocs.io/en/latest/

https://github.com/tusharkolekar24/rudraya

## Contributing
Contributions in any form are welcome, including:
- Documentation improvements
- Additional tests
- New features to existing models
- New models

