Hands-On Data Analysis with Pandas

Classification

The goal of classification is to determine how to label data using a set of discrete labels. This probably sounds similar to supervised clustering; however, in this case, we don't care how close members of the groups are spatially. Instead, we concern ourselves with classifying them with the correct class label. Remember, in Chapter 8, Rule-Based Anomaly Detection, when we classified the IP addresses as hacker or not hacker? We didn't care how well-defined clusters of IP addresses were—we just wanted to find the hackers.

Just as with regression, scikit-learn provides many algorithms for classification tasks. These are spread across modules, but will usually say Classifier at the end for classification tasks, as opposed to ...