Invention Grant
US08478542B2 Non-parametric modeling apparatus and method for classification, especially of activity state 有权
非参数建模装置和分类方法,特别是活动状态

Non-parametric modeling apparatus and method for classification, especially of activity state
Abstract:
The activity state classification method of the present invention employs a kernel-based modeling technique, and more specifically a set of similarity-based models, which have been created using example data, to process an input observation or set of input observations, each comprising a set of sensor readings or “features” derived there from or other data, to predict the activity state of a person from whom the sensor data was obtained. A model is created for each class of activity. The input data is processed by each model and the resulting predictions are combined to yield a final prediction of which state of activity is represented by the input data.
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