Abstract: An adaptable classification method is provided. The method performs the classification by using a classification standard having a plurality of categories. The classification standard is classified into different categories based on probability ranges. The adaptable classification method includes training a classifying device with a plurality of samples and using the trained classifying device to determine the categories of the samples to obtain classification model scores of the samples, transferring, by using logistic-like functions, the classification model scores into probability values; and adjusting parameters of logistic-like functions to iterate the training of the classifying device such that the probability values conform to value ranges corresponding to categories of the classification standard.

Abstract: An adaptable classification method is provided. The method performs the classification by using a classification standard having a plurality of categories. The classification standard is classified into different categories based on probability ranges. The adaptable classification method includes training a classifying device with a plurality of samples and using the trained classifying device to determine the categories of the samples to obtain classification model scores of the samples, transferring, by using logistic-like functions, the classification model scores into probability values; and adjusting parameters of logistic-like functions to iterate the training of the classifying device such that the probability values conform to value ranges corresponding to categories of the classification standard.