iprior (version 0.7.4)

tecator.cv: Results of I-prior cross-validation experiment on Tecator data set

Description

Results of I-prior cross-validation experiment on Tecator data set

Usage

tecator.cv

Format

Results from iprior_cv cross validation experiment. This is a list of seven, with each component bearing the results for the linear, quadratic, cubic, fBm-0.5, fBm-MLE and SE I-prior models. The seventh is a summarised table of the results.

Details

For the fBm and SE kernels, it seems numerical issues arise when using a direct optimisation approach. Terminating the algorithm early (say using a relaxed stopping criterion) seems to help.

Examples

# Results from the six experiments
print(tecator.cv[[1]], "RMSE")
print(tecator.cv[[2]], "RMSE")
print(tecator.cv[[3]], "RMSE")
print(tecator.cv[[4]], "RMSE")
print(tecator.cv[[5]], "RMSE")
print(tecator.cv[[6]], "RMSE")

# Summary of results
print(tecator.cv[[7]])

if (FALSE) {

# Prepare data set
data(tecator, package = "caret")
endpoints <- as.data.frame(endpoints)
colnames(endpoints) <- c("water", "fat", "protein")
absorp <- -t(diff(t(absorp)))  # this takes first differences using diff()
fat <- endpoints$fat

# Here is the code to replicate the results
mod1.cv <- iprior_cv(fat, absorp, folds = Inf)
mod2.cv <- iprior_cv(fat, absorp, folds = Inf, kernel = "poly2",
                     est.offset = TRUE)
mod3.cv <- iprior_cv(fat, absorp, folds = Inf, kernel = "poly3",
                     est.offset = TRUE)
mod4.cv <- iprior_cv(fat, absorp, method = "em", folds = Inf, kernel = "fbm",
                     control = list(stop.crit = 1e-2))
mod5.cv <- iprior_cv(fat, absorp, folds = Inf, kernel = "fbm",
                     est.hurst = TRUE, control = list(stop.crit = 1e-2))
mod6.cv <- iprior_cv(fat, absorp, folds = Inf, kernel = "se",
                     est.lengthscale = TRUE, control = list(stop.crit = 1e-2))

tecator_res_cv <- function(mod) {
  res <- as.numeric(apply(mod$res[, -1], 2, mean))  # Calculate RMSE
  c("Training RMSE" = res[1], "Test RMSE" = res[2])
}

tecator_tab_cv <- function() {
  tab <- t(sapply(list(mod1.cv, mod2.cv, mod3.cv, mod4.cv, mod5.cv, mod6.cv),
                  tecator_res_cv))
  rownames(tab) <- c("Linear", "Quadratic", "Cubic", "fBm-0.5", "fBm-MLE",
                     "SE-MLE")
  tab
}

tecator.cv <- list(
  "linear"   = mod1.cv,
  "qudratic" = mod2.cv,
  "cubic"    = mod3.cv,
  "fbm-0.5"  = mod4.cv,
  "fbm-MLE"  = mod5.cv,
  "SE"       = mod6.cv,
  "summary"  = tecator_tab_cv()
)
}