PHP MCordingley\Regression\Algorithm\GradientDescent\Schedule Namespace

Interfaces

Name Description
Schedule

Classes

Name Description
Adagrad Automatically tunes the step size of for each feature. Features with steep slopes will get rapidly get smaller steps while features with shallow slopes will get larger steps. Either way, the step size for each feature is strictly decreasing over time.
Adam Adam, or "Adaptive Moment Estimation", is another schedule that automatically tunes the step sizes for each coefficient. It builds on the theoretical foundation of RmsProp and addresses some issues that RMSProp and Adagrad have. This is the currently recommended implementation for adaptive gradients and should be safe to use without manual tuning of the constructor parameters.
Fixed Simple step rule that always provides a fixed step size to the descent.
RmsProp Essentially takes a moving average of the squares of the gradient and uses that to calculate step sizes. As with Adagrad, steeper slopes lead to smaller step sizes while shallower slopes lead to larger step sizes. Unlike Adagrad, step sizes are not necessarily strictly decreasing.