Unsupervised learning with the soft-means algorithm
Chris Thornton · 2002
This note describes a useful adaptation of the 'peak seeking' regime used in unsupervised learning processes such as competitive learning and 'k-means'. The adaptation enables the learning to capture low-order probability effects and thus to more fully capture the probabilistic structure of the training data.>