resultsMultipleKernelGreedySearch {GreedyExperimentalDesign}

Returns the results (thus far) of the greedy design search for multiple kernels

Description

Returns the results (thus far) of the greedy design search for multiple kernels

Usage

resultsMultipleKernelGreedySearch(obj, max_vectors = 9, form = "one_zero")

Arguments

obj

The greedy_multiple_kernel_experimental_design object that is currently running the search

max_vectors

The number of design vectors you wish to return. NULL returns all of them. This is not recommended as returning over 1,000 vectors is time-intensive. The default is 9.

form

Which form should it be in? The default is one_zero for 1/0's or pos_one_min_one for +1/-1's.

Author(s)

Adam Kapelner

Examples

 ## Not run: 
	library(MASS)
	data(Boston)
 #pretend the Boston data was an experiment setting 
	#first pull out the covariates
 X = Boston[, 1 : 13]
 #begin the greedy design search
	ged = initGreedyMultipleKernelExperimentalDesignObject(X, 
		max_designs = 1000, num_cores = 3, kernel_names = c("mahalanobis", "gaussian"))
	#wait
	res = resultsMultipleKernelGreedySearch(ged, max_vectors = 2)
	design = res$ending_indicTs[, 1] #ordered already by best-->worst
 design
	#how far have we come of the 1000 we set out to do?
	ged
	#we can cut it here
	stopSearch(ged)
	
## End(Not run)