modelselect

Name	modelselect JSON
Version	0.0.1 JSON
	download
home_page	https://github.com/shoukewei/modelselect
Summary	A package helps select independent variables for traditional linear regression models
upload_time	2022-12-24 04:36:17
maintainer
docs_url	None
author	Shouke Wei
requires_python
license	MIT License
keywords	python linear regression statsmodels model improvement select variables insignificant multicollinearity
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # modelselect

A package helps easily create an optimal linear regression model by removing the insignificant and multicollinearity predictor variables, which can help you reduce the interactive process and tedious work to run the model, estimate it, evaluate it, reestimate and reevaluate it, etc. 

Developed by Shouke Wei from Deepsim Academy, Deepsim Intelligence Technology Inc. (c) 2022

## Install the package
```python
pip install modelselect
```

## import the package
```python
from modelselect import LRSelector
```
then use the `LRSelector()` directly. Or 
```python
import modelselect as ms
```
then use `ms.LRSelector()`

## Document
An example: https://github.com/shoukewei/modelselect/blob/main/docs/example.ipynb



            

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