Bagged Boosted Trees for Classification of Ecological Momentary Assessment Data [article]

Gerasimos Spanakis and Gerhard Weiss and Anne Roefs
2016 arXiv   pre-print
Ecological Momentary Assessment (EMA) data is organized in multiple levels (per-subject, per-day, etc.) and this particular structure should be taken into account in machine learning algorithms used in EMA like decision trees and its variants. We propose a new algorithm called BBT (standing for Bagged Boosted Trees) that is enhanced by a over/under sampling method and can provide better estimates for the conditional class probability function. Experimental results on a real-world dataset show
more » ... at BBT can benefit EMA data classification and performance.
arXiv:1607.01582v1 fatcat:v5iftcuhbrbibbvslbuevfbkse