Class: FSelector::BaseCFS
- Defined in:
- lib/fselector/algo_base/base_CFS.rb
Overview
for simplicity, we use sequential forward search for optimal feature subset, the original CFS that uses best first search only produces slightly better results but demands much more computational resources
base class for Correlation-based Feature Selection (CFS) algorithm, see specialized versions for discrete feature (CFS_d) and continuous feature (CFS_c), respectively.
ref: Feature Selection for Discrete and Numeric Class Machine Learning
Instance Method Summary collapse
-
#initialize(data = nil) ⇒ BaseCFS
constructor
initialize from an existing data structure.
Methods inherited from Base
#algo_type, #each_class, #each_feature, #each_sample, #get_class_labels, #get_classes, #get_data, #get_data_copy, #get_feature_ranks, #get_feature_scores, #get_feature_type, #get_feature_values, #get_features, #get_opt, #get_sample_size, #select_feature!, #select_feature_by_rank!, #select_feature_by_score!, #set_classes, #set_data, #set_feature_type, #set_features, #set_opt
Methods included from ReplaceMissingValues
#replace_by_fixed_value!, #replace_by_knn_value!, #replace_by_mean_value!, #replace_by_median_value!, #replace_by_most_seen_value!
Methods included from FileIO
#data_from_csv, #data_from_libsvm, #data_from_random, #data_from_url, #data_from_weka, #data_to_csv, #data_to_libsvm, #data_to_weka
Constructor Details
#initialize(data = nil) ⇒ BaseCFS
initialize from an existing data structure
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# File 'lib/fselector/algo_base/base_CFS.rb', line 17 def initialize(data=nil) super(data) end |