Dot (Scalar/Inner) Product

The dot product of two vectors has a few very specific applications
(usually when the angle between vectors in required); It most often
appears when using 'the kernel trick' as an input for a neural network
or some other classifier. The kernel trick essentially states that
instead of using an input case's vector directly as the NN input, we
asses the K-nearest neighbours, using the distance-to-classes vector as
our NN input.  Effectively using the output of a KNN as the input of an
NN.