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Regression Tree Classification for Activity Prediction in Smart Homes by Bryan Minor; Diane J. Cook is a scholarly article available to read on EtoBox.

What is Regression Tree Classification for Activity Prediction in Smart Homes about?

The growing number of older adults in the population has created an increasing need for health-assistive systems, including prompting interventions to provide activity reminders. In this paper, we present a new regression-tree-based activity forecasting algorithm to predict the occurrence of future activities for prompting initiation of such activities. This automated algorithm extracts high-level features from sensor events and inputs these features to a machine learning algorithm which forecasts when a target activity will next occur. We compare this system to a standard linear regression classification using real data from smart homes. The forecasting algorithm is shown to provide lower error rates over the linear regression model.

Author

Bryan Minor; Diane J. Cook

Publisher

ACM

Published

2014

Language

EN