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.
Este exercício faz parte do curso
Analyzing IoT Data in Python
Instruções do exercício
- Import
LogisticRegressionfromsklearn.linear_model. - Initialize the model as
logreg. - Fit the model to
X_trainwith the labelsy_train. - Predict some classes using
X_test.
Exercício interativo prático
Experimente este exercício completando este código de exemplo.
# Import LogisticRegression
from ____ import ____
# Initialize the model
logreg = ____
# Fit the model
____.____(____, ____)
# Predict classes
print(____.____(____))