whaleOptimization: Whale Optimization Algorithm (Binary Whale Optimization Algorithm)

Description

Generates a search function based on the whale optimization algorithm. This function is called internally within the searchAlgorithm function. Binary Whale Optimization Algorithm Kumar2018FSinR is an algorithm that simulates the social behavior of humpback whales. This algorithm employs a binary version of the bubble-net hunting strategy. The algorithm starts with an initial population of individuals, and in each iteration updates the individuals according to several possible actions: Encircling prey, Bubble-net attacking or Search for prey

Usage

whaleOptimization(population = 10, iter = 10, verbose = FALSE)

Arguments

population

The number of whales population

iter

The number of iterations of the algorithm

verbose

Print the partial results in each iteration

Value

Returns a search function that is used to guide the feature selection process.

References

Examples

Run this code

# NOT RUN {
## The direct application of this function is an advanced use that consists of using this 
# function directly and performing a search process in a feature space
## Classification problem

# Generates the filter evaluation function
filter_evaluator <- filterEvaluator('determinationCoefficient')

# Generates the search function with WOA
woa_search <- whaleOptimization()
# Performs the search process directly (parameters: dataset, target variable and evaluator)
woa_search(iris, 'Species', filter_evaluator)
# }