Definition of the [ClusterKernel] class

Share:

Description

This class defines a Kernel mixture Model (KMM).

Details

This class inherits from the [IClusterModel] class. A Kernel mixture model is a mixture model of the form:

f({x}|\boldsymbol{θ}) =∑_{k=1}^K p_k ∏_{j=1}^d φ(x_j;σ^2_{k}) \quad x \in {R}^d.

Some constraints can be added to the variances in order to reduce the number of parameters.

Slots

component

A [ClusterKernelComponent] with the dim and standard deviation of the kernel mixture model.

rawData

A matrix with the original data set

kernelName

string with the name of the kernel to use. Possible values: "gaussian", "polynomial", "exponential". Default is "gaussian".

kernelParameters

vector with the parameters of the kernel.

Author(s)

Serge Iovleff

See Also

[IClusterModel] class

Examples

1
2
3
getSlots("ClusterKernel")
data(geyser)
new("ClusterKernel", data=geyser)

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.