Thuật ngữ AI
Từ điển đầy đủ về Trí tuệ nhân tạo
Rule Extraction
Algorithmic process that transforms the decisions of complex models like neural networks into sets of logical rules understandable by humans, facilitating the interpretation and validation of predictions.
Rule Pruning
Simplification technique that eliminates superfluous or redundant conditions in extracted rules to improve their interpretability while preserving their predictive power.
Rule Fidelity
Quantitative measure indicating to what extent the extracted rules faithfully reproduce the decisions of the original complex model, ensuring that the explanation remains consistent with the actual system behavior.
IF-THEN Rules
Fundamental logical structure in rule extraction where each IF condition (antecedent) triggers a THEN consequence (consequent), allowing an intuitive representation of decision processes.
Rule Coverage
Metric evaluating the proportion of instances in a dataset correctly classified or explained by a set of rules, thus measuring the comprehensiveness of the extracted rule system.
Decision Tree Extraction
Specific technique that converts decision paths in trees into sets of discrete rules, where each root-to-leaf path becomes an independent logical rule.
Rule Stability
Property measuring the consistency of extracted rules in the face of slight variations in input data or the model, ensuring the robustness and reliability of generated explanations.
Rule Generalization
Abstraction process that broadens the scope of specific rules to make them more universal, by removing overly restrictive conditions while maintaining their predictive relevance.
Cross-validation of rules
Evaluation methodology that tests the performance and generalizability of extracted rules on multiple data subsets, avoiding overfitting and ensuring their robustness.
Rule complexity
Quantitative measure of the number of conditions and nested structure in extracted rules, directly impacting their interpretability for non-technical end users.
Conflicting rules
Situation where two or more rules generate incompatible conclusions for the same input conditions, requiring conflict resolution mechanisms to maintain system consistency.
Post-hoc extraction
Rule extraction approach applied after complete training of a complex model, without modifying its original architecture, unlike intrinsically interpretable methods.