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


[Up] [Top]

Documentation for package ‘niarules’ version 0.2.0

Help Pages

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