Instance-Based Learning Algorithms
Machine Learning
BoosTexter: A Boosting-based Systemfor Text Categorization
Machine Learning - Special issue on information retrieval
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
Multiple-Instance Learning for Natural Scene Classification
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Collective multi-label classification
Proceedings of the 14th ACM international conference on Information and knowledge management
Multilabel Neural Networks with Applications to Functional Genomics and Text Categorization
IEEE Transactions on Knowledge and Data Engineering
The challenge problem for automated detection of 101 semantic concepts in multimedia
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
ML-KNN: A lazy learning approach to multi-label learning
Pattern Recognition
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)
Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)
Decision trees for hierarchical multi-label classification
Machine Learning
Learning multi-label alternating decision trees from texts and data
MLDM'03 Proceedings of the 3rd international conference on Machine learning and data mining in pattern recognition
Guest editors' introduction: special issue of selected papers from ECML PKDD 2009
Data Mining and Knowledge Discovery
Guest editors' introduction: Special Issue from ECML PKDD 2009
Machine Learning
Combining Instance-Based Learning and Logistic Regression for Multilabel Classification
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
Multilabel classification with meta-level features
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Multi-label learning by exploiting label dependency
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Sparse representation: extract adaptive neighborhood for multilabel classification
PRICAI'10 Proceedings of the 11th Pacific Rim international conference on Trends in artificial intelligence
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part I
Designing a multi-label kernel machine with two-objective optimization
AICI'10 Proceedings of the 2010 international conference on Artificial intelligence and computational intelligence: Part I
Multi-dimensional classification with Bayesian networks
International Journal of Approximate Reasoning
Enhancing multi-label music genre classification through ensemble techniques
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
A multilabel text classification algorithm for labeling risk factors in SEC form 10-K
ACM Transactions on Management Information Systems (TMIS)
Aggregating independent and dependent models to learn multi-label classifiers
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part II
On the stratification of multi-label data
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III
Finding patterns in behavioral observations by automatically labeling forms of wikiwork in Barnstars
Proceedings of the 7th International Symposium on Wikis and Open Collaboration
Automated feature generation from structured knowledge
Proceedings of the 20th ACM international conference on Information and knowledge management
Graphical feature selection for multilabel classification tasks
IDA'11 Proceedings of the 10th international conference on Advances in intelligent data analysis X
An efficient multi-label support vector machine with a zero label
Expert Systems with Applications: An International Journal
Multilabel classification using heterogeneous ensemble of multi-label classifiers
Pattern Recognition Letters
Improving multilabel classification performance by using ensemble of multi-label classifiers
MCS'10 Proceedings of the 9th international conference on Multiple Classifier Systems
Multi-label weighted k-nearest neighbor classifier with adaptive weight estimation
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part II
Preference-Based CBR: first steps toward a methodological framework
ICCBR'11 Proceedings of the 19th international conference on Case-Based Reasoning Research and Development
An extensive experimental comparison of methods for multi-label learning
Pattern Recognition
Improving multi-label classifiers via label reduction with association rules
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part II
Multi-label classification using conditional dependency networks
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
LIFT: multi-label learning with label-specific features
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Bayesian chain classifiers for multidimensional classification
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Multilabel classifiers with a probabilistic thresholding strategy
Pattern Recognition
Learning tree structure of label dependency for multi-label learning
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
Exploiting label dependency for hierarchical multi-label classification
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
Multi-label ensemble based on variable pairwise constraint projection
Information Sciences: an International Journal
Fast multi-label core vector machine
Pattern Recognition
Hamming selection pruned sets (HSPS) for efficient multi-label video classification
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
Multi-label lego -- enhancing multi-label classifiers with local patterns
IDA'12 Proceedings of the 11th international conference on Advances in Intelligent Data Analysis
Image annotation by semi-supervised cross-domain learning with group sparsity
Journal of Visual Communication and Image Representation
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
An efficient probabilistic framework for multi-dimensional classification
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Integrated instance- and class-based generative modeling for text classification
Proceedings of the 18th Australasian Document Computing Symposium
Dependent binary relevance models for multi-label classification
Pattern Recognition
Random block coordinate descent method for multi-label support vector machine with a zero label
Expert Systems with Applications: An International Journal
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Multilabel classification is an extension of conventional classification in which a single instance can be associated with multiple labels. Recent research has shown that, just like for conventional classification, instance-based learning algorithms relying on the nearest neighbor estimation principle can be used quite successfully in this context. However, since hitherto existing algorithms do not take correlations and interdependencies between labels into account, their potential has not yet been fully exploited. In this paper, we propose a new approach to multilabel classification, which is based on a framework that unifies instance-based learning and logistic regression, comprising both methods as special cases. This approach allows one to capture interdependencies between labels and, moreover, to combine model-based and similarity-based inference for multilabel classification. As will be shown by experimental studies, our approach is able to improve predictive accuracy in terms of several evaluation criteria for multilabel prediction.