Can anybody offer an explanation as to why an image of a tiger can have a confidence score of 99% as a tiger but only 84% confidence score as an animal. I guess the system has no concept of taxonomy.
The classifiers were probably trained independently and are running independently here as well, not in a hierarchical fashion.
Another way of saying this is that while the tiger training data consisted completely of tigers (for positive training examples), the animal training data might not have had any tigers at all (however unlikely) -- i.e. it could be recognizing the tiger image as containing similar enough features to the images of dogs and cats and lions that it did see to trigger the animal classifier, but with only 84% confidence.
Another way of saying this is that while the tiger training data consisted completely of tigers (for positive training examples), the animal training data might not have had any tigers at all (however unlikely) -- i.e. it could be recognizing the tiger image as containing similar enough features to the images of dogs and cats and lions that it did see to trigger the animal classifier, but with only 84% confidence.