Instance-Based Learning Algorithms
Machine Learning
A practical approach to feature selection
ML92 Proceedings of the ninth international workshop on Machine learning
The power of sampling in knowledge discovery
PODS '94 Proceedings of the thirteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Estimating attributes: analysis and extensions of RELIEF
ECML-94 Proceedings of the European conference on machine learning on Machine Learning
A sequential algorithm for training text classifiers
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Improving Generalization with Active Learning
Machine Learning - Special issue on structured connectionist systems
Selective Sampling Using the Query by Committee Algorithm
Machine Learning
Selection of relevant features and examples in machine learning
Artificial Intelligence - Special issue on relevance
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
Multidimensional access methods
ACM Computing Surveys (CSUR)
A study of support vectors on model independent example selection
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Visualization and interactive feature selection for unsupervised data
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Feature selection in unsupervised learning via evolutionary search
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Text Classification from Labeled and Unlabeled Documents using EM
Machine Learning - Special issue on information retrieval
An Algorithm for Finding Best Matches in Logarithmic Expected Time
ACM Transactions on Mathematical Software (TOMS)
Customer Retention via Data Mining
Artificial Intelligence Review - Issues on the application of data mining
Machine Learning
Feature Selection for Knowledge Discovery and Data Mining
Feature Selection for Knowledge Discovery and Data Mining
Instance Selection and Construction for Data Mining
Instance Selection and Construction for Data Mining
Overcoming the Myopia of Inductive Learning Algorithms with RELIEFF
Applied Intelligence
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Use of Contextual Information for Feature Ranking and Discretization
IEEE Transactions on Knowledge and Data Engineering
Database Mining: A Performance Perspective
IEEE Transactions on Knowledge and Data Engineering
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Toward Optimal Active Learning through Sampling Estimation of Error Reduction
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Comprehensible Interpretation of Relief's Estimates
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Feature selection for high-dimensional genomic microarray data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
An adaptation of Relief for attribute estimation in regression
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
On Feature Selection: Learning with Exponentially Many Irrelevant Features as Training Examples
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Active Learning for Natural Language Parsing and Information Extraction
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Attribute Dependencies, Understandability and Split Selection in Tree Based Models
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Feature Selection as a Preprocessing Step for Hierarchical Clustering
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Feature Subset Selection and Order Identification for Unsupervised Learning
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Less is More: Active Learning with Support Vector Machines
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Filters, Wrappers and a Boosting-Based Hybrid for Feature Selection
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Feature Selection with Selective Sampling
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Dimensionality Reduction of Unsupervised Data
ICTAI '97 Proceedings of the 9th International Conference on Tools with Artificial Intelligence
Theoretical and Empirical Analysis of ReliefF and RReliefF
Machine Learning
Support vector machine active learning with applications to text classification
The Journal of Machine Learning Research
The impact of sample reduction on PCA-based feature extraction for supervised learning
Proceedings of the 2006 ACM symposium on Applied computing
Process-Specific Information for Learning Electronic Negotiation Outcomes
Fundamenta Informaticae
Feature selection and classification model construction on type 2 diabetic patients' data
Artificial Intelligence in Medicine
Improving the Detection of Unknown Computer Worms Activity Using Active Learning
KI '07 Proceedings of the 30th annual German conference on Advances in Artificial Intelligence
OWA-weighted based clustering method for classification problem
Expert Systems with Applications: An International Journal
Feature selection with dynamic mutual information
Pattern Recognition
Classification Algorithm Based on Feature Selection and Samples Selection
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
An optimization of ReliefF for classification in large datasets
Data & Knowledge Engineering
ReliefMSS: a variation on a feature ranking ReliefF algorithm
International Journal of Business Intelligence and Data Mining
Correlation-based feature ranking for online classification
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Tuning ReliefF for genome-wide genetic analysis
EvoBIO'07 Proceedings of the 5th European conference on Evolutionary computation, machine learning and data mining in bioinformatics
Large scale instance selection by means of a parallel algorithm
IDEAL'10 Proceedings of the 11th international conference on Intelligent data engineering and automated learning
Learning to ask the right questions to help a learner learn
Proceedings of the 16th international conference on Intelligent user interfaces
Predicting high-risk program modules by selecting the right software measurements
Software Quality Control
Feature evaluation and selection with cooperative game theory
Pattern Recognition
Feature selection for MAUC-oriented classification systems
Neurocomputing
Editorial: Large scale instance selection by means of federal instance selection
Data & Knowledge Engineering
A RELIEF-based modality weighting approach for multimodal information retrieval
Proceedings of the 2nd ACM International Conference on Multimedia Retrieval
Process-Specific Information for Learning Electronic Negotiation Outcomes
Fundamenta Informaticae
Feature selection using dynamic weights for classification
Knowledge-Based Systems
Nonnegative Least-Squares Methods for the Classification of High-Dimensional Biological Data
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Simultaneous sample and gene selection using t-score and approximate support vectors
PRIB'13 Proceedings of the 8th IAPR international conference on Pattern Recognition in Bioinformatics
CAAC -- An Adaptive and Proactive Access Control Approach for Emergencies in Smart Infrastructures
ACM Transactions on Autonomous and Adaptive Systems (TAAS) - Special Section on Best Papers from SEAMS 2012
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Feature selection, as a preprocessing step to machine learning, has been very effective in reducing dimensionality, removing irrelevant data, increasing learning accuracy, and improving result comprehensibility. Traditional feature selection methods resort to random sampling in dealing with data sets with a huge number of instances. In this paper, we introduce the concept of active feature selection, and investigate a selective sampling approach to active feature selection in a filter model setting. We present a formalism of selective sampling based on data variance, and apply it to a widely used feature selection algorithm Relief. Further, we show how it realizes active feature selection and reduces the required number of training instances to achieve time savings without performance deterioration. We design objective evaluation measures of performance, conduct extensive experiments using both synthetic and benchmark data sets, and observe consistent and significant improvement. We suggest some further work based on our study and experiments.