Metadata-Version: 2.1
Name: analyticsdf
Version: 0.0.4.3
Summary: Analytic generation of datasets with specified statistical characteristics.
Home-page: https://github.com/Faye-yufan/analytics-dataset
Author: Fei
Author-email: Yufan Fei <yufanfei@usc.edu>, Eli Wang <eliwangc@gmail.com>
License: MIT License        
        Copyright (c) 2022 Faye-yufan        
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Project-URL: Homepage, https://github.com/Faye-yufan/analytics-dataset
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: scipy

Analytic generation of datasets with specified statistical characteristics.

# Introduction
analytics-dataset provides a set of functionality to enable the specification and generation of a wide range of datasets with specified statistical characteristics. Specification to include the predictor matrix and the response vector  
Examples include:
* High correlation and multi-collinearity among predictor variables
* Interaction effects between variables
* Skewed distributions of predictor and response variables
* Nonlinear relationships between predictor and response variables

## Research existing automate dataset functionality
* Sklearn [Make Datasets](https://scikit-learn.org/stable/datasets/sample_generators.html) functionality
* MIT Synthetic Data Vault project
  * [MIT Data to AI Lab](https://dai.lids.mit.edu/)
  * [datacebo](https://datacebo.com/)
  * 2016 IEEE conference paper, The Synthetic Data Vault. 
