phi.gaussian: Transform Function for Gaussian Kernel Approximation

In DPpack: Differentially Private Statistical Analysis and Machine Learning

Transform Function for Gaussian Kernel Approximation

Description

This function maps an input data row x with a given prefilter to an output value in such a way as to approximate the Gaussian kernel \insertCitechaudhuri2011DPpack.

Usage

phi.gaussian(x, theta)

Arguments

x	Vector or matrix corresponding to one row of the dataset X.
theta	Randomly sampled prefilter vector of length n+1, where n is the length of x.

Value

Mapped value corresponding to one element of the transformed space.

References

\insertRef

chaudhuri2011DPpack

Examples

  x <- c(1,2,3)
  theta <- c(0.1, 1.1, -0.8, 3)
  phi.gaussian(x, theta)

DPpack documentation built on April 8, 2023, 9:09 a.m.