Explora: a multipattern and multistrategy discovery assistant
Advances in knowledge discovery and data mining
Machine Learning
Machine Learning
An Algorithm for Multi-relational Discovery of Subgroups
PKDD '97 Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery
Mining Association Rules in Multiple Relations
ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
Database dependency discovery: a machine learning approach
AI Communications
Involving Aggregate Functions in Multi-relational Search
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
A Pathology of Bottom-Up Hill-Climbing in Inductive Rule Learning
ALT '02 Proceedings of the 13th International Conference on Algorithmic Learning Theory
On Semantic Properties of Interestingness Measures for Extracting Rules from Data
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I
A Novel Rule Ordering Approach in Classification Association Rule Mining
MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
A Unified View of Objective Interestingness Measures
MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
Evaluation Measures for Multi-class Subgroup Discovery
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
Interestingness of Association Rules Using Symmetrical Tau and Logistic Regression
AI '09 Proceedings of the 22nd Australasian Joint Conference on Advances in Artificial Intelligence
A statistical interestingness measures for XML based association rules
PRICAI'10 Proceedings of the 11th Pacific Rim international conference on Trends in artificial intelligence
IEEE Transactions on Fuzzy Systems
Interestingness measures for association rules based on statistical validity
Knowledge-Based Systems
Estimating the difficulty level of the challenges proposed in a competitive e-learning environment
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part I
Measuring media-based social interactions provided by smartphone applications in social networks
SBNMA '11 Proceedings of the 2011 ACM workshop on Social and behavioural networked media access
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Why is rule learning optimistic and how to correct it
ECML'06 Proceedings of the 17th European conference on Machine Learning
Quality-Aware association rule mining
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
From local to global patterns: evaluation issues in rule learning algorithms
LPD'04 Proceedings of the 2004 international conference on Local Pattern Detection
Local patterns: theory and practice of constraint-based relational subgroup discovery
LPD'04 Proceedings of the 2004 international conference on Local Pattern Detection
Knowledge-Based sampling for subgroup discovery
LPD'04 Proceedings of the 2004 international conference on Local Pattern Detection
Mining correlated rules for associative classification
ADMA'05 Proceedings of the First international conference on Advanced Data Mining and Applications
Inductive querying for discovering subgroups and clusters
Proceedings of the 2004 European conference on Constraint-Based Mining and Inductive Databases
Multiobjective evolutionary induction of subgroup discovery fuzzy rules: a case study in marketing
ICDM'06 Proceedings of the 6th Industrial Conference on Data Mining conference on Advances in Data Mining: applications in Medicine, Web Mining, Marketing, Image and Signal Mining
Classification based on specific rules and inexact coverage
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A media-based social interactions analysis procedure
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Heuristic rule-based regression via dynamic reduction to classification
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Compile the Hypothesis Space: Do it Once, Use it Often
Fundamenta Informaticae - Progress on Multi-Relational Data Mining
Interestingness measures for fixed consequent rules
IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
Measuring media-based social interactions in online civicmobilization against corruption in Brazil
Proceedings of the 18th Brazilian symposium on Multimedia and the web
Multiplicity and word sense: evaluating and learning from multiply labeled word sense annotations
Language Resources and Evaluation
Media-based social interaction patterns: a case study in an online civic mobilization
Proceedings of the 2012 international workshop on Socially-aware multimedia
Optimonotone Measures For Optimal Rule Discovery
Computational Intelligence
AIMSA'12 Proceedings of the 15th international conference on Artificial Intelligence: methodology, systems, and applications
A taxonomy of privacy-preserving record linkage techniques
Information Systems
BruteSuppression: a size reduction method for Apriori rule sets
Journal of Intelligent Information Systems
CAR-NF: A classifier based on specific rules with high netconf
Intelligent Data Analysis
Behavior-based clustering and analysis of interestingness measures for association rule mining
Data Mining and Knowledge Discovery
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Numerous measures are used for performance evaluation in machine learning. In predictive knowledge discovery, the most frequently used measure is classification accuracy. With new tasks being addressed in knowledge discovery, new measures appear. In descriptive knowledge discovery, where induced rules are not primarily intended for classification, new measures used are novelty in clausal and subgroup discovery, and support and confidence in association rule learning. Additional measures are needed as many descriptive knowledge discovery tasks involve the induction of a large set of redundant rules and the problem is the ranking and filtering of the induced rule set. In this paper we develop a unifying view on some of the existing measures for predictive and descriptive induction. We provide a common terminology and notation by means of contingency tables. We demonstrate how to trade off these measures, by using what we call weighted relative accuracy. The paper furthermore demonstrates that many rule evaluation measures developed for predictive knowledge discovery can be adapted to descriptive knowledge discovery tasks.