Early Transition Detection-a Dynamic Extension to Common Classification Methods
نویسندگان
چکیده
An extension for classi cation methods in order to process time-dependent data is introduced. It is based on the detection of transitions from one steady state to another one by examination of the time derivatives of classi cation vectors. The method is called Early Transition Detection. It is shown that it can be used in conjunction with a number of common classi cation methods like SIMCA or Arti cial Neural Nets and it is successfully tested on simulated and on real data.
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