The weighted k-NN classification algorithm has received increased attention recently for two reasons. First, by using neural autoencoding, k-NN can deal with mixed numeric and non-numeric predictor ...

In many scenarios, using L1 regularization drives some neural network weights to 0, leading to a sparse network. Using L2 regularization often drives all weights to small values, but few weights ...