Estimating attributes: analysis and extensions of RELIEF
ECML-94 Proceedings of the European conference on machine learning on Machine Learning
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
Enhanced word clustering for hierarchical text classification
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Mlps (mono layer polynomials and multi layer perceptrons) for nonlinear modeling
The Journal of Machine Learning Research
Ranking a random feature for variable and feature selection
The Journal of Machine Learning Research
Feature extraction by non parametric mutual information maximization
The Journal of Machine Learning Research
Smart Environments: Technology, Protocols and Applications (Wiley Series on Parallel and Distributed Computing)
Inferring Activities from Interactions with Objects
IEEE Pervasive Computing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Activity Recognition and Monitoring Using Multiple Sensors on Different Body Positions
BSN '06 Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks
Location-based activity recognition using relational Markov networks
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Keeping the resident in the loop: adapting the smart home to the user
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Human Activity Recognition and Pattern Discovery
IEEE Pervasive Computing
Feature Selection with Ensembles, Artificial Variables, and Redundancy Elimination
The Journal of Machine Learning Research
Detecting individual activities from video in a smart home
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part I
The feature selection problem: traditional methods and a new algorithm
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Error bounds for convolutional codes and an asymptotically optimum decoding algorithm
IEEE Transactions on Information Theory
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The data mining and pervasive sensing technologies found in smart homes offer unprecedented opportunities for providing health monitoring and assistance to individuals experiencing difficulties in living independently at home. In order to monitor the functional health of smart home residents, we need to design technologies that recognize and track activities that people normally perform as part of their daily routines. One question that frequently arises, however, is how many smart home sensors are needed and where should they be placed in order to accurately recognize activities? We employ data mining techniques to look at the problem of sensor selection for activity recognition in smart homes. We analyze the results based on six datasets collected in five distinct smart home environments. © 2011 John Wiley & Sons, Inc. WIREs Data Mining Knowl Discov 2011 1 339–351 DOI: 10.1002/widm.20