Orthogonal Decision Trees for Resource-Constrained Physiological Data Stream Monitoring Using Mobile Devices

Several challenging new applications demand the ability to do data mining on resource constrained devices. One such application is that of monitoring physiological data streams obtained from wearable sensing devices. Such monitoring has applications for pervasive healthcare management, be it for seniors, emergency response personnel, soldiers in the battlefield or atheletes. A key requirement is that the monitoring system be able to run on resouce constrained handheld or wearable devices. Orthogonal decision trees (ODTs) offer an effective way to construct a redundancy-free, accurate, and meaningful representation of large decision-tree-ensembles often created by popular techniques such as Bagging, Boosting, Random Forests and many distributed and data stream mining algorithms. Orthogonal decision trees are functionally orthogonal to each other and they correspond to the principal components of the underlying function space. This paper discusses various properties of the ODTs and the...

• Type: Conference
• Year: 2005
• Where: HIPC
• Authors: Haimonti Dutta, Hillol Kargupta, Anupam Joshi
• Keywords: HIPC 2005, Orthogonal Decision Trees, Physiological Data Streams, Resource Constrained Devices