Pattern Classification

Representation at the Hidden Layer• What do the learned weights mean?• The weights connecting hidden layer to outputlayer form a linear discriminant• The weights connecting input layer to hiddenlayer represent a mapping from the inputfeature space to a latent feature space• For each hidden unit, the weights from inputlayer describe the input pattern that leads tothe maximum activation of that node