DTAnalyzer

class pyruleanalyzer.DTAnalyzer(classifier: RuleClassifier)

Decision-Tree-specific rule analysis and comparison.

This class extracts the DT analysis pipeline out of RuleClassifier and adds redundancy breakdown tracking so the output shows:

• intra_tree – boundary-redundant sibling pairs merged

• low_usage – rules removed because of low classification count

classifier

The underlying RuleClassifier instance.

redundancy_counts

Dict mapping redundancy type to count.

compare_initial_final_results(file_path: str) → None

Compares performance of initial vs final rules for a Decision Tree.

Evaluates both rule sets on the test data, displays metrics, logs divergent cases, and writes a detailed report.

Parameters:

file_path – Path to the CSV test file.

execute_rule_analysis(file_path: str, remove_below_n_classifications: int = -1) → None

Evaluates DT rules on a dataset, detects redundancies, and refines.

This method: 1. Classifies every sample to gather per-rule usage stats. 2. Optionally removes low-usage rules (with sibling promotion). 3. Tracks redundancy counts by type. 4. Writes a report and saves the final model.

Parameters:

• file_path – Path to the CSV test file.

• remove_below_n_classifications – Threshold for low-usage pruning (-1 disables).

print_redundancy_summary() → None

Prints the redundancy breakdown and rule reduction summary.

track_intra_tree_from_duplicates(duplicated_rules_pairs: list) → None

Updates the intra_tree counter from duplicate-pair detection.

Called by RuleClassifier.execute_rule_analysis() after the duplicate-removal loop finishes for DT.

Parameters:

duplicated_rules_pairs – List of (rule1, rule2) tuples found by find_duplicated_rules.