This function uses default or user supplied ojective functions, rank functions, to evaluate fitness of a generation chromosomes. This process can be parallized if nCores > 1
. Parallel operations uses mclapply
to parallelize operations. Max number of parallel operations is determined by detectCores
. Prescheduling = TRUE is only option for compuations. It is advised to only use parallelization if inputed a large dataframe with great than 1000 oberations and/or predictors.
1 2 | evaluate_fitness(generation_t0, Y, X, family, nCores, minimize,
objective_function, rank_objective_function)
|
generation_t0 |
a matrix of parent chromosomes to be evaluated. Columns correspond to predictors/genes and rows correspond to parents/chromosomes. |
Y |
vector of response variable |
X |
a matrix or dataframe of predictor variables |
family |
a character string describing the error distribution and link function to be used in the model. Default is gaussian. |
nCores |
an integer indicating number of parallel processes to run when evaluating fitness. See |
minimize |
a logical value indicating whether optimize should be minimized (TRUE) or maximized (FALSE). |
objective_function |
function for computing objective. Default is |
rank_objective_function |
a function that ranks parents by their fitness as determined by optimize criteria. This function uses |
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