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Linear regression attempts to model the relationship between variables by fitting a linear equation to observed data.

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Awesome Linear Regression

Awesome Linear Regression 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.

About Awesome Linear Regression

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

First contact with Awesome Linear Regression

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))

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You can ask questions and join the development discussion:


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Linear regression attempts to model the relationship between variables by fitting a linear equation to observed data.

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