A method of resume-training of discontinuous wear state trackers for composing boosting high-accurate ensembles needed to regard statistical data inaccuracies and shifts
Vadim V. Romanuke, В.В. Романюк · Electronic Archive Khmelnitskiy National University (Khmelnitskiy National University) · 2015
For tracking metal wear states at bad statistical data inaccuracies and shifts, there is a method of resume-training of discontinuous wear state trackers for boosting them within high-accurate ensembles. These trackers are Gaussian-noiseddata- trained two-layer perceptrons. An ordinary tracker is selected and, if its performance is satisfactory, it is resumed-trained cyclically. Number of additional passes of training sets is limited. The resume-training procedure wholly can be cycled.