C115 Logistic regression Exp.txt

The numpy.ravel() function returns contiguous flattened 
array(1D array with all the input-array elements and with 
the same type as it). 

x = np.array([[1, 3, 5], [11, 35, 56]])  
y=np.ravel(x)  
y  


The coef_ contain the coefficients for the prediction of each 
of the targets. It is also the same as if you trained a model 
to predict each of the targets separately. (it's the slope)


the intercept_, shows the point where the estimated 
regression line crosses the 𝑦 axis. (Y-intercept c)


The numpy.linspace() function returns number spaces 
evenly w.r.t interval.