Numerical Association Rule Mining using Population-Based Nature-Inspired Algorithms

Documentation for package ‘niarules’ version 0.2.0

add_attribute	Add an attribute to the "rule" list.
build_rule	Build rules based on a candidate solution.
calculate_border	Calculate the border value based on feature information and a given value.
calculate_fitness	Calculate the fitness of an association rule.
calculate_selected_category	Calculate the selected category based on a value and the number of categories.
check_attribute	Check if the attribute conditions are satisfied for an instance.
cut_point	Calculate the cut point for an association rule.
differential_evolution	Implementation of Differential Evolution metaheuristic algorithm.
evaluate	Evaluate a candidate solution, with optional time series filtering.
extract_feature_info	Extract feature information from a dataset, excluding timestamps.
feature_position	Get the position of a feature.
fix_borders	Fix Borders of a Numeric Vector
format_rule_parts	Format Rule Parts
map_to_ts	Map solution boundaries to time series instances.
print_association_rules	Print Numerical Association Rules
print_feature_info	Print feature information extracted from a dataset.
problem_dimension	Calculate the dimension of the problem, excluding timestamps.
read_dataset	Read a CSV Dataset
rs	Simple Random Search
supp_conf	Calculate support and confidence for an association rule.
write_association_rules_to_csv	Write Association Rules to CSV file