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Rule Quality Measures Settings in a Sequential Covering Rule Induction Algorithm - an Empirical Approach
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Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/1098-111x(200101)16:1<13::aid-int3>3.0.co;2-mopenalex-snapshot
Induction of decision rules in classification and discovery-oriented perspectives
inferredcites →https://doi.org/10.1002/1098-111x(200101)16:1<13::aid-int3>3.3.co;2-dopenalex-snapshot
Induction of decision rules in classification and discovery‐oriented perspectives
inferredcites →https://doi.org/10.1007/11677437_1openalex-snapshot
Generality Is Predictive of Prediction Accuracy
inferredcites →https://doi.org/10.1007/11908029_74openalex-snapshot
Rule Quality Measures in Creation and Reduction of Data Rule Models
inferredcites →https://doi.org/10.1007/3-540-48751-4_17openalex-snapshot
Rule Evaluation Measures: A Unifying View
inferredcites →https://doi.org/10.1007/3-540-48912-6_64openalex-snapshot
An Analysis of Quantitative Measures Associated with Rules
inferredcites →https://doi.org/10.1007/978-0-387-09823-4openalex-snapshot
Data Mining and Knowledge Discovery Handbook
inferredcites →https://doi.org/10.1007/978-0-387-09823-4_30openalex-snapshot
Interestingness Measures - On Determining What Is Interesting
inferredcites →https://doi.org/10.1007/978-3-540-45231-7_22openalex-snapshot
APRIORI-SD: Adapting Association Rule Learning to Subgroup Discovery
inferredcites →https://doi.org/10.1007/978-3-540-48247-5_21openalex-snapshot
Taming Large Rule Models in Rough Set Approaches
inferredcites →https://doi.org/10.1007/978-3-642-11479-3_8openalex-snapshot
Decision Rule-Based Data Models Using TRS and NetTRS – Methods and Algorithms
inferredcites →https://doi.org/10.1007/978-3-642-13529-3_3openalex-snapshot
RSCTC’2010 Discovery Challenge: Mining DNA Microarray Data for Medical Diagnosis and Treatment
inferredcites →https://doi.org/10.1007/978-3-642-21881-1_44openalex-snapshot
Data-Driven Adaptive Selection of Rules Quality Measures for Improving the Rules Induction Algorithm
inferredcites →https://doi.org/10.1007/978-3-642-23014-1_4openalex-snapshot
Context-Based Service Recommendation for Assisting Business Process Design
inferredcites →https://doi.org/10.1007/978-3-7908-1853-6openalex-snapshot
Fuzzy and Neuro-Fuzzy Intelligent Systems
inferredcites →https://doi.org/10.1007/s10618-008-0089-yopenalex-snapshot
PRIE: a system for generating rulelists to maximize ROC performance
inferredcites →https://doi.org/10.1007/s10618-010-0177-7openalex-snapshot
ENDER: a statistical framework for boosting decision rules
inferredcites →https://doi.org/10.1007/s10844-010-0121-8openalex-snapshot
A review and comparison of strategies for handling missing values in separate-and-conquer rule learning
inferredcites →https://doi.org/10.1007/s10994-005-5011-xopenalex-snapshot
ROC ?n? Rule Learning?Towards a Better Understanding of Covering Algorithms
inferredcites →https://doi.org/10.1007/s10994-009-5162-2openalex-snapshot
On the quest for optimal rule learning heuristics
inferredcites →https://doi.org/10.1016/b978-1-55860-377-6.50023-2openalex-snapshot
Fast Effective Rule Induction
inferredcites →https://doi.org/10.1016/j.engappai.2004.04.008openalex-snapshot
Can Bayesian confirmation measures be useful for rough set decision rules?
inferredcites →https://doi.org/10.1016/j.engappai.2006.11.015openalex-snapshot
Mining Pareto-optimal rules with respect to support and confirmation or support and anti-support
inferredcites →https://doi.org/10.1016/j.ins.2010.10.030openalex-snapshot
Sequential covering rule induction algorithm for variable consistency rough set approaches
inferredcites →https://doi.org/10.1016/j.patrec.2005.10.010openalex-snapshot
An introduction to ROC analysis
inferredcites →https://doi.org/10.1017/cbo9780511498497openalex-snapshot
The Foundations of Causal Decision Theory
inferredcites →https://doi.org/10.1017/s0269888905000408openalex-snapshot
A survey of interestingness measures for knowledge discovery
inferredcites →https://doi.org/10.1023/a:1006524209794openalex-snapshot
Separate-and-Conquer Rule Learning
inferredcites →https://doi.org/10.1080/03081079.2013.798901openalex-snapshot
Data-driven adaptive selection of rule quality measures for improving rule induction and filtration algorithms
inferredcites →https://doi.org/10.1111/0824-7935.00154openalex-snapshot
Rule Quality Measures for Rule Induction Systems: Description and Evaluation
inferredcites →https://doi.org/10.1145/1014052.1014090openalex-snapshot
Exploiting a support-based upper bound of Pearson's correlation coefficient for efficiently identifying strongly correlated pairs
inferredcites →https://doi.org/10.1145/1132960.1132963openalex-snapshot
Interestingness measures for data mining
inferredcites →https://doi.org/10.1145/130385.130401openalex-snapshot
A training algorithm for optimal margin classifiers
inferredcites →https://doi.org/10.1145/775047.775053openalex-snapshot
Selecting the right interestingness measure for association patterns
inferredcites →https://doi.org/10.1613/jair.1089openalex-snapshot
Expert-Guided Subgroup Discovery: Methodology and Application
inferredcites →https://doi.org/10.21936/si2013_v34.n2b.71openalex-snapshot
Program do indukcji i oceny reguł klasyfikacyjnych, zintegrowany z pakietem R
inferredcites →https://doi.org/10.2307/2670132openalex-snapshot
Machine Learning and Statistics: The Interface
inferredcites →https://doi.org/10.2307/2678411openalex-snapshot
The Foundations of Causal Decision Theory
inferredcites →https://doi.org/10.3233/fi-2014-956openalex-snapshot
Relationships Between Length and Coverage of Decision Rules
inferredcites →https://doi.org/10.3233/ida-2003-7203openalex-snapshot
Rule quality for multiple-rule classifier: Empirical expertise and theoretical methodology1
inferredcites →https://doi.org/10.3233/ifs-2012-0564openalex-snapshot
Decision rule length as a basis for evaluation of attribute relevance
inferredcites →https://doi.org/10.4018/ijswis.2014010102openalex-snapshot
Pattern Based Feature Construction in Semantic Data Mining
inferredcites →https://doi.org/10.5555/1005332.1005338openalex-snapshot
Subgroup Discovery with CN2-SD
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-030-02357-7_2openalex-snapshot
Weighting Attributes and Decision Rules Through Rankings and Discretisation Parameters
inferred← citeshttps://doi.org/10.1007/978-3-030-77967-2_15openalex-snapshot
Improvement of Random Undersampling to Avoid Excessive Removal of Points from a Given Area of the Majority Class
inferred← citeshttps://doi.org/10.1007/978-3-031-37720-4_13openalex-snapshot
New Approach to Constructive Induction—Towards Deep Discrete Learning
inferred← citeshttps://doi.org/10.1007/978-3-319-60438-1_33openalex-snapshot
Filtering Decision Rules with Continuous Attributes Governed by Discretisation
inferred← citeshttps://doi.org/10.1007/978-3-319-60837-2_28openalex-snapshot
On Combining Discretisation Parameters and Attribute Ranking for Selection of Decision Rules
inferred← citeshttps://doi.org/10.1016/j.eswa.2021.115437openalex-snapshot
Privacy preserving rule-based classifier using modified artificial bee colony algorithm
inferred← citeshttps://doi.org/10.1016/j.procs.2019.09.167openalex-snapshot
The Proposal of Undersampling Method for Learning from Imbalanced Datasets
inferred← citeshttps://doi.org/10.1016/j.procs.2022.09.399openalex-snapshot
New Undersampling Method Based on the kNN Approach
inferred← citeshttps://doi.org/10.22362/ijcert/2018/v5/i1/v5i102openalex-snapshot
Review of Rule Quality Measurement: Metrics and Rule Evaluation Models
inferred← citeshttps://doi.org/10.5755/j01.itc.48.4.22330openalex-snapshot
An Adaptive Hybrid Ant Colony Optimization Algorithm for The Classification Problem
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