Graph-Based Algorithms for Boolean Function Manipulation
IEEE Transactions on Computers
International Journal of Man-Machine Studies - Special Issue: Knowledge Acquisition for Knowledge-based Systems. Part 5
Learnability and the Vapnik-Chervonenkis dimension
Journal of the ACM (JACM)
C4.5: programs for machine learning
C4.5: programs for machine learning
Overcoming the Myopia of Inductive Learning Algorithms with RELIEFF
Applied Intelligence
R-MINI: An Iterative Approach for Generating Minimal Rules from Examples
IEEE Transactions on Knowledge and Data Engineering
IEEE Expert: Intelligent Systems and Their Applications
Machine Learning
Consecutive Interval Query and Dynamic Programming on Intervals
ISAAC '93 Proceedings of the 4th International Symposium on Algorithms and Computation
Dynamic Programming on Intervals
ISA '91 Proceedings of the 2nd International Symposium on Algorithms
Linear-Time Preprocessing in Optimal Numerical Range Partitioning
Journal of Intelligent Information Systems - Special issue: A survey of research questions for intelligent information systems in education
Overcoming the Myopia of Inductive Learning Algorithms with RELIEFF
Applied Intelligence
Parallel Formulations of Decision-Tree Classification Algorithms
Data Mining and Knowledge Discovery
R-MINI: An Iterative Approach for Generating Minimal Rules from Examples
IEEE Transactions on Knowledge and Data Engineering
IEEE Transactions on Knowledge and Data Engineering
Binary Rule Generation via Hamming Clustering
IEEE Transactions on Knowledge and Data Engineering
A Unified Framework for Evaluation Metrics in Classification Using Decision Trees
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
The Use of Domain Knowledge in Feature Construction for Financial Time Series Prediction
EPIA '01 Proceedings of the10th Portuguese Conference on Artificial Intelligence on Progress in Artificial Intelligence, Knowledge Extraction, Multi-agent Systems, Logic Programming and Constraint Solving
Ensemble Feature Selection Based on Contextual Merit and Correlation Heuristics
ADBIS '01 Proceedings of the 5th East European Conference on Advances in Databases and Information Systems
Ensemble Feature Selection Based on the Contextual Merit
DaWaK '01 Proceedings of the Third International Conference on Data Warehousing and Knowledge Discovery
Direct Domain Knowledge Inclusion in the PA3 Rule Induction Algorithm
PAKDD '01 Proceedings of the 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining
Correlation-Based and Contextual Merit-Based Ensemble Feature Selection
IDA '01 Proceedings of the 4th International Conference on Advances in Intelligent Data Analysis
Transforming data to satisfy privacy constraints
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Theoretical and Empirical Analysis of ReliefF and RReliefF
Machine Learning
Efficient Multisplitting Revisited: Optima-Preserving Elimination of Partition Candidates
Data Mining and Knowledge Discovery
Data-intensive analytics for predictive modeling
IBM Journal of Research and Development
A selective sampling approach to active feature selection
Artificial Intelligence
On Efficient Handling of Continuous Attributes in Large Data Bases
Fundamenta Informaticae
Evaluation of ordinal attributes at value level
Data Mining and Knowledge Discovery
Feature salience definition and estimation and its use in feature subset selection
Intelligent Data Analysis
Combining Answers of Sub-classifiers in the Bagging-Feature Ensembles
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
Concepts for novelty detection and handling based on a case-based reasoning process scheme
Engineering Applications of Artificial Intelligence
A General Framework of Feature Selection for Text Categorization
MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
CSNL: A cost-sensitive non-linear decision tree algorithm
ACM Transactions on Knowledge Discovery from Data (TKDD)
Concepts for novelty detection and handling based on a case-based reasoning process scheme
ICDM'07 Proceedings of the 7th industrial conference on Advances in data mining: theoretical aspects and applications
Data mining on multimedia data
Data mining on multimedia data
Artificial Intelligence in Medicine
A new method for discretization of continuous attributes based on VPRS
RSCTC'06 Proceedings of the 5th international conference on Rough Sets and Current Trends in Computing
Large-margin feature selection for monotonic classification
Knowledge-Based Systems
Feature selection for MAUC-oriented classification systems
Neurocomputing
On Efficient Handling of Continuous Attributes in Large Data Bases
Fundamenta Informaticae
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Deriving classification rules or decision trees from examples is an important problem. When there are too many features, discarding weak features before the derivation process is highly desirable. When there are numeric features, they need to be discretized for the rule generation. We present a new approach to these problems. Traditional techniques make use of feature merits based on either the information theoretic, or the statistical correlation between each feature and the class. We instead assign merits to features by finding each feature's "obligation" to the class discrimination in the context of other features. The merits are then used to rank the features, select a feature subset, and discretize the numeric variables. Experience with benchmark example sets demonstrates that the new approach is a powerful alternative to the traditional methods. This paper concludes by posing some new technical issues that arise from this approach.