Logistic Regression
Using the data from the previous exercise, you'll now train a Machine learning model.
In line with best practices, the data is now available as X_train
, while the labels have been loaded as y_train
.
A subset of the data is also available as X_test
. You'll learn later in this chapter how to properly create these variables.
Cet exercice fait partie du cours
Analyzing IoT Data in Python
Instructions
- Import
LogisticRegression
fromsklearn.linear_model
. - Initialize the model as
logreg
. - Fit the model to
X_train
with the labelsy_train
. - Predict some classes using
X_test
.
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de code.
# Import LogisticRegression
from ____ import ____
# Initialize the model
logreg = ____
# Fit the model
____.____(____, ____)
# Predict classes
print(____.____(____))