Rotating hyperplane is a stream generator that generates d-dimensional classification problems in which the prediction is defined by a rotating hyperplane. By changing the orientation and position of the hyperplane over time in a smooth manner, we can introduce smooth concept drift.
This version is created with MOA library with drift parameters t equal to 0.1 (control the magnitude of change after every instance) within a window of 100k. Probability of reversing change direction is fixed at 10%.
It contains 500k instances with 10 numeric features. 5% noise is added by randomly changing the class labels.