Week 3_3 - Simple Logistic Regression

Hi everyone. Can anybody answer to my question?

Is the Simple Logistic Regression which is discussed in the 3rd part in this notebook(week3) ,written by one line code —>>>

clf = sklearn.linear_model.LogisticRegressionCV()

is the same as Logistic Regression with a Neural Network mindset (week 2 notebook)

Or in the Simple logistic regression we do not use any activation??

Is there any differences between this 2 regressions?

Hi, the implementation of the simple logistic regression in week 2 notebook is done with neural networks, however, the LogisticRegressionCV algorithm of sklearn relies on a different mathematical approach which do not need any activation function.

You can see the source code of LogisticRegressionCV here. In the class definition they’ve included the following:

This class implements logistic regression using liblinear, newton-cg, sag of lbfgs optimizer