Classification with guaranteed probability of error
نویسندگان
چکیده
منابع مشابه
Frequency domain uncertainty sets with guaranteed probability level in Prediction Error Identification †
A model G(z, θ̂) identified in the Prediction Error (PE) framework [6] is always an approximation of the real-life system G(z, θ0) we want to identify. A model is therefore useless if it is not accompanied with information about the achieved error G(z, θ̂)−G(z, θ0). A classical domain where it is convenient to express the features of this error is the frequency domain (i.e. the Nyquist plane). In...
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ژورنال
عنوان ژورنال: Machine Learning
سال: 2010
ISSN: 0885-6125,1573-0565
DOI: 10.1007/s10994-010-5183-x