|
|
|
Early Stopping: Machine Learning, Neural Network, Gradient Descent, Training Set, VC Dimension
|
(Buch) |
Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!
| Lieferstatus: |
 i.d.R. innert 7-14 Tagen versandfertig |
| Veröffentlichung: |
März 2026
|
| Genre: |
Ratgeber |
| ISBN: |
9786131173462 |
|
EAN-Code:
|
9786131173462 |
| Verlag: |
Omniscriptum |
| Einband: |
Kartoniert |
| Sprache: |
English
|
| Dimensionen: |
H 220 mm / B 150 mm / D 4 mm |
| Gewicht: |
113 gr |
| Seiten: |
64 |
| Bewertung: |
Titel bewerten / Meinung schreiben
|
| Inhalt: |
| Please note that the content of this book primarily consists of articles
available from Wikipedia or other free sources online. In machine
learning, early stopping is a form of regularization used when a machine
learning model (such as a neural network) is trained by on-line gradient
descent. In early stopping, the training set is split into a new
training set and a validation set. Gradient descent is applied to the
new training set. After each sweep through the new training set, the
network is evaluated on the validation set. When the performance with
the validation test stops improving, the algorithm halts. The network
with the best performance on the validation set is then used for actual
testing, with a separate set of data (the validation set is used in
learning to decide when to stop). |
|
Newsfeed | 
Facebook | 
Twitter
