1. An adaptable classification method having a classification standard of a plurality of categories that are classifiable according to probability values, the adaptable classification method comprising: (1) providing a plurality of samples to train a classifying device; (2) determining categories of the samples, by using the trained classifying device, to obtain classification model scores of the samples; (3) transferring the classification model scores into probability values by logistic-like functions having parameters, and classifying the probability values into the categories based on the classification standard; and (4) determining whether the probability values conform to value ranges corresponding to the categories of the classification standard, and stopping training the classifying device if the probability values conform to the value ranges, or adjusting the parameters of the logistic-like functions and transferring the classification model scores into new probability values by the adjusted logistic-like functions and iterating step (4) to determine whether the new probability values conform to the value ranges.