In this chapter, we'll learn how to make predictions with scikit-learn. Machine learning emphasizes on measuring the ability to predict, and with scikit-learn we will predict accurately and quickly.
We will examine the iris dataset, which consists of measurements of three types of Iris flowers: Iris Setosa, Iris Versicolor, and Iris Virginica.
To measure the strength of the predictions, we will:
- Save some data for testing
- Build a model using only training data
- Measure the predictive power on the test set
The prediction—one of three flower types is categorical. This type of problem is called a classification problem.
Informally, classification asks, Is it an apple or an orange? Contrast this with machine learning regression, ...
