Supervised Learning for Streaming Data
Sayan Putatunda · Apress eBooks · 2021
In the last chapter, you learned some concept drift detection algorithms. This chapter focuses on supervised learning algorithms (for classification tasks and regression tasks) in a streaming data context. In supervised learning, there is a target or a response variable and there are predictor variables. The goal of the learner/model is to understand the relationship between the target and the predictor variables. This can then be used to make predictions on the target variable for future observations of the predictor variables [1]. (I assume that you are already familiar with the supervised learning techniques used in a batch setting.)