Feature Engineering Made Easy

Creating a baseline machine learning pipeline

In previous chapters, we offered to you, the reader, a single machine learning model to use throughout the chapter. In this chapter, we will do some work to find the best machine learning model for our needs and then work to enhance that model with feature selection. We will begin by importing four different machine learning models:

• Logistic Regression
• K-Nearest Neighbors
• Decision Tree
• Random Forest

The code for importing the learning models is given as follows:

# Import four machine learning modelsfrom sklearn.linear_model import LogisticRegressionfrom sklearn.neighbors import KNeighborsClassifierfrom sklearn.tree import DecisionTreeClassifierfrom sklearn.ensemble import RandomForestClassifier ...