klaR (version 0.6-12)

benchB3: Benchmarking on B3 data

Description

Evaluates the performance of a classification method on the B3 data.

Usage

benchB3(method, prior = rep(1/4, 4), sv = "4", scale = FALSE, ...)

Arguments

method
classification method to use
prior
prior probabilities of classes
sv
class of the start of a business cycle
scale
logical, whether to use scale first
...
furhter arguments passed to method

Value

A list with elements
MODEL
list with the model returned by method of the training data
error
vector of test error rates in cycles
l1co.error
leave-one-cycle-out error rate

Details

The performance of classification methods on cyclic data can be measured by a special form of cross-validation: Leave-One-Cycle-Out. That means that a complete cycle is used as test data and the others are used as training data. This is repeated for all complete cycles in the data.

See Also

B3

Examples

Run this code
perLDA <- benchB3("lda")
## Not run: 
# ## due to parameter optimization rda takes a while 
# perRDA <- benchB3("rda")
# library(rpart)
# ## rpart will not work with prior argument:
# perRpart <- benchB3("rpart", prior = NULL)
# ## End(Not run)

Run the code above in your browser using DataLab