I have one output factor with values from 0 to 1. Like you rightfully said, I will use the output values from each goat to classify the images into 3 distinct classes, i.e. class A for values less than 0.30, class B from 0.30 to 0.70 and class C greater than 0.70. However, because I have grouped my data into 3 distinct and mutually exclusive classes, I’m likely going to have biases for images from goats with percentages such as 0.28, 0.32, 0.69 or 0.73 as they are close to my delineating points and may give predictions belonging to another group. Therefore, I would want to use Multi-label classification for such figures (ie +/- 0.05 from 0.3 and from 0.7). Would this work, if not what other deep learning method would work for such a prediction analysis