First steps with scikit-learn
In Chapter 2, Training Machine Learning Algorithms for Classification, you learned about two related learning algorithms for classification: the perceptron rule and Adaline, which we implemented in Python by ourselves. Now we will take a look at the scikit-learn API, which combines a user-friendly interface with a highly optimized implementation of several classification algorithms. However, the scikit-learn library offers not only a large variety of learning algorithms, but also many convenient functions to preprocess data and to fine-tune and evaluate our models. We will discuss this in more detail together with the underlying concepts in Chapter 4, Building Good Training Sets – Data Preprocessing, and Chapter 5, Compressing Data via Dimensionality Reduction.
Training a perceptron via scikit-learn
To get started with the scikit-learn library, we will train a perceptron model similar to the one that we implemented in Chapter 2, Training Machine Learning...
