An awesome package that allows getting meaningful information from a Linear regression model
Project description
Reg2info
reg2info is a Python package for getting meaningful information from a Linear regression model.
Table of content
Where to get it
Binary installers for the latest released version are available at the Python Package Index (PyPI)
Use the package manager pip to install reg2info :
pip install reg2info
Dependencies
- Numpy
- Matplotlib
Main Features
-
A linear regression line has an equation of the form Y = a + bX, where X is the explanatory variable and Y is the dependent variable. The slope of the line is b, and a is the intercept (the value of y when x = 0).
-
A regression line is the “best fit” line for your data. You basically draw a line that best represents the data points. It’s like an average of where all the points line up. In linear regression, the regression line is a perfectly straight line.
Usage
import reg2info as r2i
lr = LinearRegression().fit(X_train, y_train)
# returns equation
eq = r2i.reg_equation(lr)
# returns line and data plot
plot = r2i.reg_plot(lr,X_train[feature], y_train)
Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
License
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