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An adaptive modular approach to the mining of sensor network data G. Bontempi, Y. Le Borgne (1) {gbonte,yleborgn}@ulb.ac.be Machine Learning Group Université Libre de Bruxelles – Belgium (1) Supported by the COMP 2 SYS project, sponsored by the HRM program of the European Community (MEST-CT-2004-505079)
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object]
Sensor networks : Overview ,[object Object],[object Object],[object Object],[object Object],[object Object]
Smart dust project ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Current available sensors ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Applications ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Challenges for… ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Machine learning and WSN ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Machine learning and WSN ,[object Object],[object Object],[object Object]
Supervised learning and WSN ,[object Object],[object Object],[object Object]
A supervised learning scenario ,[object Object],[object Object],[object Object],[object Object],[object Object]
Centralized approach High transmission overhead
Two-layer approach ,[object Object],[object Object],[object Object],[object Object]
Two-layer adaptive approach ,[object Object],[object Object]
Compression : PCA ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
PAST – Recursive PCA ,[object Object],[object Object],[object Object],[object Object]
PAST Algorithm Recursive formulation: [HYV01]
Learning algorithm ,[object Object],[object Object],[object Object],[object Object],[object Object]
How many neighbours? ,[object Object],[object Object],[object Object]
How many neighbours? ,[object Object]
How many neighbours? ,[object Object],[object Object]
How many neighbours? ,[object Object],[object Object],[object Object]
How many neighbours? ,[object Object],[object Object],[object Object],[object Object]
How many neighbours? ,[object Object],[object Object],[object Object],[object Object],[object Object]
Automatic model selection ([BIR99],[BON99],[BON00]) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Advantages of PAST and lazy ,[object Object],[object Object],[object Object],[object Object]
Simulation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Test procedure ,[object Object],[object Object],[object Object],Example of learning curve:
Experiment 1 ,[object Object],[object Object]
Results ,[object Object],0.115 0.124 0.132 0.196 0.183 0.223 0.257 0.363 0.782 NMSE PAST 0.116 0.124 0.133 0.134 0.138 0.144 0.181 0.266 0.621 NMSE PCA 16 12 8 6 5 4 3 2 1 m
Clustering ,[object Object],[object Object],[object Object],[object Object]
Experiment 2 ,[object Object],[object Object],[object Object],[object Object],Example of P (2) partitioning
Results ,[object Object],[object Object],[object Object],[object Object],0.114 0.116 0.118 0.118 0.118 0.140 NMSE P (7) P (6) P (5) P (4) P (3) P (2)
Experiment 3 ,[object Object],[object Object],[object Object],[object Object],[object Object]
Results ,[object Object],[object Object],0.117 0.116 0.116 0.119 0.132 0.501 NMSE P (7) P (6) P (5) P (4) P (3) P (2)
Experiment 4 ,[object Object],[object Object],[object Object],[object Object],[object Object]
Results ,[object Object],[object Object]
Conclusion ,[object Object],[object Object],[object Object],[object Object],[object Object]
Future work ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
References ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
References on lazy learning ,[object Object],[object Object],[object Object]
[object Object]

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"An adaptive modular approach to the mining of sensor network ...

  • 1. An adaptive modular approach to the mining of sensor network data G. Bontempi, Y. Le Borgne (1) {gbonte,yleborgn}@ulb.ac.be Machine Learning Group Université Libre de Bruxelles – Belgium (1) Supported by the COMP 2 SYS project, sponsored by the HRM program of the European Community (MEST-CT-2004-505079)
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