jul097
4/30/2020 - 8:47 AM

Using sklearn package to model data

As mentioned before, Coefficient and Intercept in the simple linear regression, are the parameters of the fit line. Given that it is a simple linear regression, with only 2 parameters, and knowing that the parameters are the intercept and slope of the line, sklearn can estimate them directly from our data. Notice that all of the data must be available to traverse and calculate the parameters.

modeldatasklean
content_copyfile_download
from sklearn import linear_model
regr = linear_model.LinearRegression()
train_x = np.asanyarray(train[['INDEPENDANTVARIABLEHERE']])
train_y = np.asanyarray(train[['DEPENDANTVARIABLEHERE']])
regr.fit (train_x, train_y)
# The coefficients
print ('Coefficients: ', regr.coef_)
print ('Intercept: ',regr.intercept_)
plt.scatter(train.INDEPENDANTVARIABLEHERE, train.DEPENDANTVARIABLEHERE,  color='blue')
plt.plot(train_x, regr.coef_[0][0]*train_x + regr.intercept_[0], '-r')
plt.xlabel("INDEPENDANTVARIABLEHERE")
plt.ylabel("DEPENDANTVARIABLEHERE")