loss_smooth: Smooth Loss A loss function for when you want gradients

In edahelsinki/slise: Sparse Linear Subset Explanations

Smooth Loss A loss function for when you want gradients

Description

Smooth Loss A loss function for when you want gradients

Usage

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

Arguments

alpha	The vector to calculate loss 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 loss value

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