LogisticRegressionCV

LogisticRegressionCV is a class that implements cross-validation inside it. This class will train multiple LogisticRegression models and return the best one.

Exercise 7.06: Training a Logistic Regression Model Using Cross-Validation

The goal of this exercise is to train a logistic regression model using cross-validation and get the optimal R2 result. We will be making use of the Cars dataset that you worked with previously.

The following steps will help you complete the exercise:

1. Open a new Colab notebook.
2. Import the necessary libraries:

   # import libraries
   import pandas as pd
   from sklearn.model_selection import train_test_split

   In this step, you import pandas and alias it as pd. You will make use of pandas to read in the file you will be working with.

3. Create headers for the data:

   # data doesn't have headers, so let's create headers
   _headers = ['buying', 'maint', 'doors', 'persons', \
    ...