Description Usage Arguments Value Author(s) References Examples
View source: R/hybridSearchGenerator.R
Generates a hybrid search function. This function in combination with the evaluator guides the feature selection process. Specifically, the result of calling this function is another function that is passed on as a parameter to the featureSelection
function. However, you can run this function directly to perform a search process in the features space.
1 | hybridSearchAlgorithm(hybridSearcher, params = list())
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hybridSearcher |
Name of the hybrid search algorithm. The available hybrid search algorithms are:
|
params |
List with the parameters of each hybrid search method. For more details see each method. Default: empty list. |
Returns a hybrid search function that is used to guide the feature selection process.
Francisco Aragón Royón
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | ## Not run:
## Examples of a hybrid search algorithm generation
hybrid_search_method <- hybridSearchAlgorithm('LCC')
## Examples of a hybrid search algorithm generation (with parameters)
hybrid_search_method <- hybridSearchAlgorithm('LCC', list(threshold = 0.8))
## The direct application of this function is an advanced use that consists of using this
# function directly to perform a hybrid search process on a feature space
## Classification problem
# Generates the first filter evaluation function (individual or set measure)
filter_evaluator_1 <- filterEvaluator('determinationCoefficient')
# Generates the second filter evaluation function (mandatory set measure)
filter_evaluator_2 <- filterEvaluator('ReliefFeatureSetMeasure')
# Generates the hybrid search function
hybrid_search_method <- hybridSearchAlgorithm('LCC')
# Run the search process directly (params: dataset, target variable, evaluator1 & evaluator2)
hybrid_search_method(iris, 'Species', filter_evaluator_1, filter_evaluator_2)
## End(Not run)
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