Comparative Study of Classification Techniques with Labeled Data in Wireless Sensor Network
The wireless sensor nodes are getting smaller, but Wireless Sensor Networks (WSNs) are getting larger with the technological developments, currently containing thousands of nodes and possibly millions of nodes in the future. To deal with the large volume of data produced by these special kinds of wireless networks, one approach is use of Data Mining techniques. Classification is an important task in data mining. Classification of sensory data is a major research problem in WSNs and it can be widely used in reducing the data transmission in WSNs effectively and also in process monitoring. In this paper, Labeled Wireless Sensor Network Data is used for mining. This multi-hop data consist of humidity and temperature measurements.