PDEnaiveBayes (version 0.2.8)

PlotLikelihoods: PlotLikelihoods

Description

Plots the Likelihoods per feature.

Usage

PlotLikelihoods(Likelihoods, Data, PlausibleLikelihoods=NULL,Epsilon=NULL,
PlausibleCenters=NULL,PlotCutOff=4,xlim)

Value

No return value.

Arguments

Likelihoods

List with Likelihoods.

Data

Numeric matrix with data.

PlausibleLikelihoods

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

Details

Boundaries are assumed to be zero for plotting.

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)

PlotLikelihoods(Likelihoods = VPDENB$Model$ListOfLikelihoods, Data = TrainX)