Application of Decision Trees to Smart Homes

  • Vlado Stankovski
  • Jernej Trnkoczy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4008)


This chapter aims to illustrate a possible way of using decision trees to make Smart Homes smarter. Decision trees are popular modelling technique, and the corresponding models are both predictive and descriptive. We formulate the modelling problem by defining the generic question “Is the undergoing activity or event in the Smart Home usual?” Then we explain how it is possible to gather appropriate data from the sensors and pre-process these data to form appropriate input for a decision tree algorithm. We further explain the mainstream approaches in decision trees algorithms rather then analysing them in detail, and we give short overview of available software. Finally, we explain some measures for quantitative and qualitative evaluation of the induced decision tree models (e.g. expert opinion, cross-validation, statistical tests etc.).


Decision Tree Smart Home Decision Tree Model Decision Tree Algorithm Induce Decision Tree 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Vlado Stankovski
    • 1
  • Jernej Trnkoczy
    • 1
  1. 1.Department of Construction Informatics, Faculty of Civil and Geodetic EngineeringUniversity of LjubljanaSlovenia

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