tidychangepoint (version 1.0.1)

fitness: Retrieve the optimal fitness (or objective function) value used by an algorithm

Description

Retrieve the optimal fitness (or objective function) value used by an algorithm

Usage

fitness(object, ...)
# S3 method for seg_basket
fitness(object, ...)
# S3 method for seg_cpt
fitness(object, ...)
# S3 method for tidycpt
fitness(object, ...)
# S3 method for ga
fitness(object, ...)
# S3 method for cpt
fitness(object, ...)
# S3 method for cga
fitness(object, ...)
# S3 method for segmented
fitness(object, ...)
# S3 method for wbs
fitness(object, ...)

Value

A named double vector with the fitness value.

Arguments

object

A segmenter object.

...

currently ignored

Details

Segmenting algorithms use a fitness metric, typically through the use of a penalized objective function, to determine which changepoint sets are more or less optimal. This function returns the value of that metric for the changepoint set implied by the object provided.

See Also

Other tidycpt-generics: as.model(), as.segmenter(), changepoints(), diagnose(), model_name()

Other segmenter-functions: as.segmenter(), model_args(), seg_params()

Examples

# Segment a times series using a genetic algorithm
x <- segment(DataCPSim, method = "ga", maxiter = 10)

# Retrieve its fitness value
fitness(x)

# \donttest{
# Segment a times series using a genetic algorithm
x <- segment(DataCPSim, method = "cga")

# Retrieve its fitness value
fitness(x)
# }
# Segment a time series using Segmented
x <- segment(DataCPSim, method = "segmented")

# Retrieve its fitness
fitness(x)

# Segment a time series using Wild Binary Segmentation
x <- segment(DataCPSim, method = "wbs")

# Retrieve its fitness
fitness(x)