I am having problems to understand the practical meaning of the union of hypthesis sets. What does the Union mean for the classification task? If we look into one example: There is one hypothesis set Ha (ha1,ha2,ha3...han) that defines a 2d perceptron. There is another hypothesis set Hb (hb1,hb2,hb3...hbn)that defines another 2d perceptron .

Now we create a set H = Ha U Hb that contains the hypothesis (ha1,ha2,ha3...han,hb1,hb2,hb3...hbn). The hypothesis set H contains more hypothesis but they are still of the same kind (according to the Union the components of the two sets are merged into one set ). What does H define? Does it define a 2d perceptron. Or does the H hypothesis define TWO 2d perceptrons that correspond to two lines? It is not clear to me how to get concrete view of the Union. Any suggestions....?