The Boosting Approach

The origin of the boosting method for designing learnign machines is traced back to the work of Valiant and Kearns, who posed the question of whether a weak learning algorithm, meaning one that does slightly better than random guessing, can be boosted into a strong one with a good performance index. At the heart of … Continue reading The Boosting Approach

Change Detection for time series signals

In general, approaches to cope with concept drift can be classified into two categories: approaches that adapt a learner at regular intervals without considering whether changes have really occurred. approaches that first detect concept changes and afterwards the learner is adapted to these changes. In the fist approach, drifting concepts are often handled by time … Continue reading Change Detection for time series signals