Machine Learning in Java - Second Edition

Reducing spurious transitions

At the end of the activity recognition pipeline, we want to make sure that the classifications are not too volatile, that is, we don't want activities to change every millisecond. A basic approach is to design a filter that ignores quick changes in the activity sequence.

We build a filter that remembers the last window activities and returns the most frequent one. If there are multiple activities with the same score, it returns the most recent one.

First, we create a new SpuriousActivityRemoval class, which will hold a list of activities and the window parameter:

class SpuriousActivityRemoval{ List<Object> last; int window; public SpuriousActivityRemoval(int window){ this.last = new ArrayList<Object>(); this.window ...