Glossary

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

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