The counterargument is, in part, that some classifiers are better than others, even when all of them satisfy the training data completely. The most obvious criterion to use is the complexity of the classifier.
The point is, probably, that humans tend to underestimate the complexity of classifiers they use. The categories like “good” are not only difficult to precisely define, they are difficult to define at all, because they are too complicated to be formulated in words. To point out that in classification we use structures based on the architecture of human brain (or whatever uniquely human) is not, in my opinion, a relativist fallacy.
To use a bit stretched analogy, to program a 3D animation on computer with an advanced graphic card and an obsolete processor may be simpler for the programmer than to program quicksort. Simplicity is not a mind-independent criterion.
The counterargument is, in part, that some classifiers are better than others, even when all of them satisfy the training data completely. The most obvious criterion to use is the complexity of the classifier.
The point is, probably, that humans tend to underestimate the complexity of classifiers they use. The categories like “good” are not only difficult to precisely define, they are difficult to define at all, because they are too complicated to be formulated in words. To point out that in classification we use structures based on the architecture of human brain (or whatever uniquely human) is not, in my opinion, a relativist fallacy.
To use a bit stretched analogy, to program a 3D animation on computer with an advanced graphic card and an obsolete processor may be simpler for the programmer than to program quicksort. Simplicity is not a mind-independent criterion.