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(a) True prediction error degrees.
(i to iii) Procedures for defining the prediction error degrees.
Therefore, ordinal regression based on KDA is used for estimating the prediction error degrees.
This subsection presents an algorithm for estimating prediction error degrees using MKDA-based ordinal regression.
Figure 5 Results of estimated prediction error degrees for the meteorological element 'temperature on the ground'.
Therefore, the proposed method estimates the prediction error degrees based on the ordinal regression.
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Then, accurate prediction error degree estimation becomes feasible.
where y is an estimated error degree by a method, and y g is a correct error degree (ground truth).
The error degree is defined as shown in Table 2. Therefore, the results of the prediction error degree have values ranging over 1,2,⋯,6,7.
Therefore, we focus on prediction error degree estimation based on ordinal regression.
Thus, it is suitable to adopt them for prediction error degree estimation.
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