PHP 클래스 MCordingley\Regression\Algorithm\GradientDescent\StoppingCriteria\GradientNorm

Good for Batch descent, when the gradient is fairly stable from one iteration to the next. Not so good for Stochastic descent and MiniBatch with small batch sizes, as those gradients won't settle near zero even as the weights converge.
상속: implements MCordingley\Regression\Algorithm\GradientDescent\StoppingCriteria\StoppingCriteria
파일 보기 프로젝트 열기: mcordingley/regression 1 사용 예제들

공개 메소드들

메소드 설명
__construct ( float $eta = 6.103515625E-5, integer $pNorm = 2 )
converged ( array $gradient, array $coefficients ) : boolean

메소드 상세

__construct() 공개 메소드

public __construct ( float $eta = 6.103515625E-5, integer $pNorm = 2 )
$eta float
$pNorm integer

converged() 공개 메소드

public converged ( array $gradient, array $coefficients ) : boolean
$gradient array
$coefficients array
리턴 boolean