Logistic regression
Let's move on to logistic regression. You'll be working with the same weather dataset again, but the goal here is to predict if it's going to rain tomorrow. We've gone ahead and created your train and test sets for you. Your dependent variables are the Humidity9am and Humidity3pm features.
It's also worth noting that the dataset has already been normalized in order to ensure that we can interpret the coefficients later on. This is always good to bring up during your interview when talking about regression for inference.
This exercise is part of the course
Practicing Statistics Interview Questions in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
from sklearn.linear_model import LogisticRegression
# Create and fit your model
clf = ____
clf.fit(____, ____)