Study the scenario and answer the question. * Assume that B is an intermediate node of a neural network, the forward propagation values of nodes A and B are 0.2 and 0.3; the associated error B of node B that was computed by the back propagation algorithm is 0.4, the learning rate is assume to be 0.5. How does the backpropagation algorithm update the weight WA,B of the edge that connects node A and B ? What is the new value of weight wA,B ? 0.24 0.34 0.44 0.14 Assume DBSCAN is run for the following dataset with MINPOINTS =3 and epsilon =5, what are the points that are not core or border points? A dataset consisting of object A, B, C, D, E, F with the following distance matrix is oiven. E and F D and F E and C A and F