Linear regression attempts to model the relationship between variables by fitting a linear equation to observed data. This repository hosts the development of the Awesome Linear Regression library.
Awesome Linear Regression , is a mathematics API written in Python. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result as fast as possible is key to doing good research.
Awesome Linear Regression is:
- Simple
- Flexible
- Powerful
The core data structures of Awesome Linear Regression are consign and result.
For installation run :
pip install Awesome-Linear-Regression
Here is an exemple
:
from Awesome_Linear_Regression import linearregression as LR
import pandas as pd
import numpy as np
# Sample training data set
x = np.matrix([[0,1],[1,4],[7,8],[50,23]])
y = np.matrix([[2],[9],[23],[96]])
# Train the model
Lr = LR(x,y)
Beta, rss = Lr.leastsquare()
Let make prediction
px = np.matrix([[4,7]])
print(Lr.predict(px))
You can ask questions and join the development discussion: