plot.nbc | R Documentation |
Plots the results from a nbc
object as a barplot
for a number of causes based on
predicted Cause Specific Mortality Fraction (CSMF).
## S3 method for class 'nbc' plot( x, top.plot = length(x$causes.pred), min.csmf = 0, csmfa.obs = NULL, footnote = TRUE, footnote.color = "gray48", footnote.size = 0.7, main = paste("Naive Bayes Classifier: Top ", top.plot, " Causes by Predicted CSMF", sep = ""), xlab = "Predicted CSMF", col = "dimgray", horiz = TRUE, border = NA, las = 1, ... )
x |
A |
top.plot |
A number that produces top k causes depending on a Cause Specific Mortality Fraction (CSMF) measure. |
min.csmf |
A number that represents the minimum CSMF measure for a cause to be included in the plot. |
csmfa.obs |
A character vector of the true causes for calculating the CSMF accuracy. |
footnote |
A boolean indicating whether to include a footnote containing details about the nbc or not. |
footnote.color |
A character specifying the color of the footnote text. |
footnote.size |
A numeric value specifying the size of the footnote text. |
main |
A character value of the title to display. |
xlab |
A character value of the x axis title. |
col |
A character value of the color to use for the plot. |
horiz |
Set to TRUE to draw bars horizontally and FALSE to draw bars vertically. |
border |
A character value of the colors to use for the bar borders. Set to NA to disable. |
las |
An integer value to determine if labels should be parallel or perpendicular to axis. |
... |
Additional arguments to be passed to |
See Methods documentation for details on CSMF and CSMF accuracy.
Generates a bar plot the top predicted causes from the NBC model
barplot
Other main functions:
nbc()
,
print.nbc_summary()
,
summary.nbc()
library(nbc4va) data(nbc4vaData) # Run naive bayes classifier on random train and test data train <- nbc4vaData[1:50, ] test <- nbc4vaData[51:100, ] results <- nbc(train, test) # Plot the top 3 causes by CSMF plot(results, top.plot=3)
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