Hands-On Machine Learning with C++

Supervised learning

Supervised ML algorithms usually take a limited set of labeled data and build models that can make reasonable predictions for new data. We can split supervised learning algorithms into two main parts, classification and regression techniques, described as follows:

• Classification models predict some finite and distinct types of categories—this could be a label that identifies if an email is spam or not, or whether an image contains a human face or not. Classification models are applied in speech and text recognition, object identification on images, credit scoring, and others. Typical algorithms for creating classification models are Support Vector Machine (SVM), decision tree approaches, k-nearest neighbors (KNN), logistic ...