Returns the results of a greedy multiple kernel search

Usage

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

Arguments

obj: The greedy_multiple_kernel_experimental_design object where the search was run.
max_vectors: How many random allocation vectors you wish to return. The default is NULL indicating you want all of them.
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

Adam Kapelner

Examples

 if (FALSE) { # \dontrun{
  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
  mk = initGreedyMultipleKernelExperimentalDesignObject(X, 
    max_designs = 100, num_cores = 3, kernel_names = c("mahalanobis", "gaussian"))
  #wait
  res = resultsMultipleKernelGreedySearch(mk, max_vectors = 2, form = "one_zero")
  res$obj_vals
  } # }