Learning to Monitoring Unsolicited Commercial Wireless Positioning

Provided by: AICIT
Topic: Software
Format: PDF
To discuss the model and search biases of the learning algorithms, along with worst-case computational complexity figures, and observe how the latter relate to experimental measurements. The authors study how classification accuracy is affected when using attributes that represent sequences of tokens, as opposed to single tokens, and explore the effect of the size of the attribute and training set, all within a cost-sensitive framework. Furthermore, based on the received radio signal strength an estimation of distance between the device and power source can be computed.

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