Feature Engineering for Modern Machine Learning with Scikit-Learn

3.3 Practical Exercises for Chapter 3

These exercises will help you practice automating data preprocessing with Scikit-learn’s Pipeline and FeatureUnion classes. Each exercise includes a solution with code for guidance.

Exercise 1: Building a Simple Pipeline with Standard Scaling and Logistic Regression

Create a pipeline that applies Standard Scaling to the numeric features Age and Income, and then uses Logistic Regression to classify a target variable Churn.

1. Load the dataset and split it into features (X) and target (y).
2. Create a pipeline with StandardScaler and LogisticRegression.
3. Train the pipeline and evaluate it on the test set.

from sklearn.pipeline import Pipeline

from sklearn.preprocessing import StandardScaler

from sklearn.linear_model ...