loss_smooth_grad: Smooth Loss Gradient Gradient for the smooth loss function

In edahelsinki/slise: Sparse Linear Subset Explanations

Smooth Loss Gradient Gradient for the smooth loss function

Description

Smooth Loss Gradient Gradient for the smooth loss function

Usage

loss_smooth_grad(
  alpha,
  X,
  Y,
  epsilon,
  beta,
  lambda1 = 0,
  lambda2 = 0,
  weight = NULL
)

Arguments

alpha	The vector to calculate loss-gradient for
X	The data matrix
Y	The response vector
epsilon	The acceptable error
beta	The steepness of the sigmoid
lambda1	The L1 regulariser (default: 0)
lambda2	The L2 regulariser (default: 0)
weight	weight vector (default: NULL)

Value

The gradients for alpha

edahelsinki/slise documentation built on Aug. 24, 2023, 11:03 p.m.