Glossary
Supervised Statistical Machine-Learning

Transfer learning

A method of reusing what has been learned on one problem as an aid to solving a slightly different one. This is commonly practiced with deep convolutional networks, by supplementing the lower layers of a pre-learned network with new layers, then performing learning iterations on a new learning base.

Supervised learning

A category of statistical learning whose aim is to empirically model an input-output relationship, based on pairs of examples (x_n, y_n) where x_n is an input vector, and y_n an associated output vector (called the desired output).

Characteristic; feature

In statistical learning, a quantity calculated from the raw inputs of the examples, and which will be the input of the learned model.

Classification; classification

One of the two subtypes of supervised learning problems, corresponding...