emil (version 2.2.3)

select: emil and dplyr integration

Description

Modeling results can be converted to tabular format and manipulated using dplyr and other Hadleyverse packages. This is accomplished by a class specific select_ function that differs somewhat in syntax from the default select_.

Usage

## S3 method for class 'list':
select_(.data, ..., .dots)
## S3 method for class 'modeling_result':
select_(.data, ..., .dots)

Value

A data.frame in long format.

See Also

subtree

Examples

# Produce some results
x <- iris[-5]
y <- iris$Species
names(y) <- sprintf("orchid%03i", seq_along(y))
cv <- resample("crossvalidation", y, nfold=3, nrepeat=2)
procedures <- list(nsc = modeling_procedure("pamr"),
                   rf = modeling_procedure("randomForest"))
result <- evaluate(procedures, x, y, resample=cv)

# Get the foldwise error for the NSC method
result %>% select(fold = TRUE, "nsc", error = "error")

# Compare both methods
require(tidyr)
result %>%
    select(fold = TRUE, method = TRUE, error = "error") %>%
    spread(method, error)
require(dplyr)
result %>%
    select(fold = TRUE, method = TRUE, error = "error") %>%
    group_by(method) %>% summarize(mean_error = mean(error))

# Investigate the variability in estimated class 2 probability across folds
result %>%
    select(fold = cv, "nsc", "prediction", probability = function(x) x$probability[,2]) %>%
    spread(fold, probability)