PDEnaiveBayes (version 0.2.8)

PlotLikelihoodFuns: PlotLikelihoodFuns

Description

Plots the class-conditional Likelihoods per feature, given the generating likelihood functions.

Usage

PlotLikelihoodFuns(LikelihoodFuns,Data,PlausibleLikelihoodFuns=NULL,
Epsilon=NULL,PlausibleCenters=NULL,PlotCutOff=4,xlim)

Value

No return value.

Arguments

LikelihoodFuns

List with Likelihoods generating functions

Data

Numeric matrix with data.

PlausibleLikelihoodFuns

List with plausible Likelihoods.

Epsilon

Numeric scalar defining epsilon fo plausible likelihoods.

PlausibleCenters

Numeric vector [1:k] plausible centers used to compute plausible likelihoods.

PlotCutOff

scalar defining the how many feature starting from 1 should be plotted or numerical vector defining the index of features to be plotted in second case should not be too many otherwise plot yields an error.

xlim

Numeric vector of length 2 stating limits of x axis.

Author

Michael Thrun

Examples

Data = as.matrix(iris[,1:4])
Cls = as.numeric(iris[,5])

TrainIdx = c(17, 73, 46, 29, 68, 35, 131, 62, 132, 127, 71, 72, 
144, 99, 93, 13, 38, 21, 102, 53, 36, 111, 114, 96, 57, 74, 145, 
86, 3, 16, 52, 59, 140, 40, 122, 109, 6, 91, 79, 15, 108, 139, 
37, 76, 20, 115, 66, 28, 100, 117, 44, 78, 80, 150, 146, 142, 
9, 90, 45, 58, 134, 11, 87, 125, 141, 118, 136, 48, 124, 47, 
8, 27, 33, 92, 130, 54, 65, 104, 23, 98, 129, 123, 34, 128, 135, 
51, 64, 5, 94, 83, 42, 116, 101, 43, 7, 12, 82, 1, 84, 138, 2, 
56, 4, 106, 120)

TestIdx = c(60, 10, 75, 70, 81, 18, 97, 95, 67, 22, 55, 143, 
88, 24, 105, 26, 119, 31, 107, 63, 41, 61, 32, 147, 89, 14, 121, 
19, 113, 49, 126, 112, 25, 77, 137, 103, 50, 30, 149, 110, 39, 
69, 148, 85, 133)

TrainX = Data[TrainIdx, ]
TestX  = Data[TestIdx, ]
TrainY = Cls[TrainIdx]
TestY  = Cls[TestIdx]

VPDENB = Train_naiveBayes(Data = TrainX, Cls = TrainY, Plausible = FALSE)

PlotLikelihoodFuns(LikelihoodFuns = VPDENB$Model$PDFs_funs, Data = TrainX)