C4.5: programs for machine learning
C4.5: programs for machine learning
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Learning decision lists using homogeneous rules
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Efficiently mining long patterns from databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Efficient mining of emerging patterns: discovering trends and differences
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient search for association rules
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Detecting Group Differences: Mining Contrast Sets
Data Mining and Knowledge Discovery
OPUS: an efficient admissible algorithm for unordered search
Journal of Artificial Intelligence Research
On the discovery of significant statistical quantitative rules
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining Minimal Distinguishing Subsequence Patterns with Gap Constraints
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
A framework to support multiple query optimization for complex mining tasks
MDM '05 Proceedings of the 6th international workshop on Multimedia data mining: mining integrated media and complex data
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Mining minimal distinguishing subsequence patterns with gap constraints
Knowledge and Information Systems
Mining statistically important equivalence classes and delta-discriminative emerging patterns
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Empirical likelihood confidence intervals for differences between two datasets with missing data
Pattern Recognition Letters
Cost-based query optimization for complex pattern mining on multiple databases
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
Contrast Set Mining for Distinguishing Between Similar Diseases
AIME '07 Proceedings of the 11th conference on Artificial Intelligence in Medicine
Conceptual equivalence for contrast mining in classification learning
Data & Knowledge Engineering
Mining influential attributes that capture class and group contrast behaviour
Proceedings of the 17th ACM conference on Information and knowledge management
Estimating confidence intervals for structural differences between contrast groups with missing data
Expert Systems with Applications: An International Journal
CSM-SD: Methodology for contrast set mining through subgroup discovery
Journal of Biomedical Informatics
Measuring the uncertainty of differences for contrasting groups
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Diverging patterns: discovering significant frequency change dissimilarities in large databases
Proceedings of the 18th ACM conference on Information and knowledge management
Engineering Applications of Artificial Intelligence
Mining negative contrast sets from data with discrete attributes
Expert Systems with Applications: An International Journal
Causal difference detection using Bayesian networks
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Contrast set mining through subgroup discovery applied to brain ischaemina data
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Ensembles of jittered association rule classifiers
Data Mining and Knowledge Discovery
On the stimulation of patterns: definitions, calculation method and first usages
ICCS'10 Proceedings of the 18th international conference on Conceptual structures: from information to intelligence
Intelligent Data Analysis
Using data mining for the refresh of learning objects digital ibraries
ICCOMP'06 Proceedings of the 10th WSEAS international conference on Computers
Using constraints to generate and explore higher order discriminative patterns
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part I
Constrained logistic regression for discriminative pattern mining
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part I
CLAP: Collaborative pattern mining for distributed information systems
Decision Support Systems
Group SAX: extending the notion of contrast sets to time series and multimedia data
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
K-optimal pattern discovery: an efficient and effective approach to exploratory data mining
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Improving data quality by source analysis
Journal of Data and Information Quality (JDIQ)
Difference detection between two contrast sets
DaWaK'06 Proceedings of the 8th international conference on Data Warehousing and Knowledge Discovery
MLDM'05 Proceedings of the 4th international conference on Machine Learning and Data Mining in Pattern Recognition
An algorithm for mining implicit itemset pairs based on differences of correlations
DS'05 Proceedings of the 8th international conference on Discovery Science
Contrast mining from interesting subgroups
Bisociative Knowledge Discovery
Explaining subgroups through ontologies
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
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Understanding the differences between contrasting groups is a fundamental task in data analysis. This realization has led to the development of a new special purpose data mining technique, contrast-set mining. We undertook a study with a retail collaborator to compare contrast-set mining with existing rule-discovery techniques. To our surprise we observed that straightforward application of an existing commercial rule-discovery system, Magnum Opus, could successfully perform the contrast-set-mining task. This led to the realization that contrast-set mining is a special case of the more general rule-discovery task. We present the results of our study together with a proof of this conclusion.