Nothing
## ----setup, echo = FALSE------------------------------------------------------
knitr::opts_chunk$set(collapse = FALSE,
comment = "#>",
prompt = FALSE,
tidy = FALSE,
echo = TRUE,
message = FALSE,
warning = FALSE,
# Default figure options:
dpi = 100,
fig.align = 'center',
fig.height = 6.0,
fig.width = 6.5,
out.width = "580px")
## ----pkgs, echo = FALSE, message = FALSE, results = 'hide'--------------------
library(FFTrees)
## ----install-pkg, eval = FALSE------------------------------------------------
# # Install the package from CRAN:
# install.packages("FFTrees")
## ----load-pkg-2, eval = TRUE, message = TRUE----------------------------------
# Load the package:
library(FFTrees)
## ----load-guide, eval = FALSE-------------------------------------------------
# # Open the main package guide:
# FFTrees.guide()
## ----fft-create, message = FALSE----------------------------------------------
# Create an FFTrees object:
heart.fft <- FFTrees(formula = diagnosis ~ ., # Criterion and (all) predictors
data = heart.train, # Training data
data.test = heart.test, # Testing data
main = "Heart Disease", # General label
decision.labels = c("Low-Risk", "High-Risk") # Decision labels (False/True)
)
## ----fft-print----------------------------------------------------------------
# Print an FFTrees object:
heart.fft
## ----fft-confusion-table, out.width="50%", echo = FALSE, fig.cap = "**Table 1**: A 2x2 confusion table illustrating the types of frequency counts for 4 possible outcomes."----
knitr::include_graphics("../inst/confusiontable.jpg")
## ----fft-plot, fig.width = 6.5, fig.height = 6--------------------------------
# Plot predictions of the best FFT when applied to test data:
plot(heart.fft, # An FFTrees object
data = "test") # data to use (i.e., either "train" or "test")?
## ----fft-no-stats, fig.width = 8, fig.height = 4, out.width = "500px"---------
# Plot only the tree, without accuracy statistics:
plot(heart.fft, what = "tree")
# plot(heart.fft, stats = FALSE) # The 'stats' argument has been deprecated.
## ----fft-cues, fig.width = 6, fig.height = 6, out.width = "500px"-------------
# Plot cue accuracies (for training data) in ROC space:
plot(heart.fft, what = "cues")
## ----fft-names----------------------------------------------------------------
# Show the names of all outputs in heart.fft:
names(heart.fft)
## ----fft-predict, eval = FALSE------------------------------------------------
# # Predict classifications for a new dataset:
# predict(heart.fft,
# newdata = heartdisease)
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