C4.5: programs for machine learning
C4.5: programs for machine learning
Machine learning, neural and statistical classification
Machine learning, neural and statistical classification
Genome analysis using clusters of orthologous groups (COGs)
RECOMB '98 Proceedings of the second annual international conference on Computational molecular biology
Separate-and-Conquer Rule Learning
Artificial Intelligence Review
Genome scale prediction of protein functional class from sequence using data mining
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
BoosTexter: A Boosting-based Systemfor Text Categorization
Machine Learning - Special issue on information retrieval
Hierarchically Classifying Documents Using Very Few Words
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Improving Text Classification by Shrinkage in a Hierarchy of Classes
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Prediction of Enzyme Classification from Protein Sequence without the Use of Sequence Similarity
Proceedings of the 5th International Conference on Intelligent Systems for Molecular Biology
A study of cross-validation and bootstrap for accuracy estimation and model selection
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Random k-Labelsets: An Ensemble Method for Multilabel Classification
ECML '07 Proceedings of the 18th European conference on Machine Learning
Ensembles of Multi-Objective Decision Trees
ECML '07 Proceedings of the 18th European conference on Machine Learning
Improved Multilabel Classification with Neural Networks
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Classification of Multi-labeled Data: A Generative Approach
ECML PKDD '08 Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II
Empirical Asymmetric Selective Transfer in Multi-objective Decision Trees
DS '08 Proceedings of the 11th International Conference on Discovery Science
Multi-label Classification with Gene Expression Programming
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
Comparing Methods for Multilabel Classification of Proteins Using Machine Learning Techniques
BSB '09 Proceedings of the 4th Brazilian Symposium on Bioinformatics: Advances in Bioinformatics and Computational Biology
ART-Based Neural Networks for Multi-label Classification
IDA '09 Proceedings of the 8th International Symposium on Intelligent Data Analysis: Advances in Intelligent Data Analysis VIII
Mining Multi-label Concept-Drifting Data Streams Using Dynamic Classifier Ensemble
ACML '09 Proceedings of the 1st Asian Conference on Machine Learning: Advances in Machine Learning
Multi-label learning by exploiting label dependency
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Combine multi-valued attribute decomposition with multi-label learning
Expert Systems with Applications: An International Journal
Mr.KNN: soft relevance for multi-label classification
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
PAKDD'09 Proceedings of the 13th Pacific-Asia international conference on Knowledge discovery and data mining: new frontiers in applied data mining
Analyzing classification methods in multi-label tasks
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part III
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
Voting based learning classifier system for multi-label classification
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
On the semantic annotation of places in location-based social networks
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part I
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
Two stage architecture for multi-label learning
Pattern Recognition
RW.KNN: a proposed random walk KNN algorithm for multi-label classification
Proceedings of the 4th workshop on Workshop for Ph.D. students in information & knowledge management
Multi-instance multi-label learning
Artificial Intelligence
Quality assessment of k-NN multi-label classification for music data
ISMIS'06 Proceedings of the 16th international conference on Foundations of Intelligent Systems
Decision trees for hierarchical multilabel classification: a case study in functional genomics
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
An efficient multi-label support vector machine with a zero label
Expert Systems with Applications: An International Journal
Some issues on detecting emotions in music
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part II
Learning classifiers using hierarchically structured class taxonomies
SARA'05 Proceedings of the 6th international conference on Abstraction, Reformulation and Approximation
Evolving multi-label classification rules with gene expression programming: a preliminary study
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part II
Multi-label classification models for sustainable flood retention basins
Environmental Modelling & Software
Learning ontology-aware classifiers
DS'05 Proceedings of the 8th international conference on Discovery Science
An extensive experimental comparison of methods for multi-label learning
Pattern Recognition
Hybrid decision tree architecture utilizing local SVMs for multi-label classification
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part II
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
A Highly Parallel Multi-class Pattern Classification on GPU
CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
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
Multilabel classification with principal label space transformation
Neural Computation
Followee recommendation in asymmetrical location-based social networks
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
Fast multi-label core vector machine
Pattern Recognition
SBIA'12 Proceedings of the 21st Brazilian conference on Advances in Artificial Intelligence
MCut: a thresholding strategy for multi-label classification
IDA'12 Proceedings of the 11th international conference on Advances in Intelligent Data Analysis
A Comparison of Multi-label Feature Selection Methods using the Problem Transformation Approach
Electronic Notes in Theoretical Computer Science (ENTCS)
Instance-Ranking: a new perspective to consider the instance dependency for classification
PAKDD'12 Proceedings of the 2012 Pacific-Asia conference on Emerging Trends in Knowledge Discovery and Data Mining
Sentiment and topic analysis on social media: a multi-task multi-label classification approach
Proceedings of the 5th Annual ACM Web Science Conference
Relational large scale multi-label classification method for video categorization
Multimedia Tools and Applications
Streamlining user interaction in tag-based conversational navigation of knowledge resource libraries
Proceedings of the 13th ACM/IEEE-CS joint conference on Digital libraries
Multi-label learning with millions of labels: recommending advertiser bid phrases for web pages
Proceedings of the 22nd international conference on World Wide Web
Ensemble multi-label learning based on neural network
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
Multilabel relationship learning
ACM Transactions on Knowledge Discovery from Data (TKDD)
Multi-label classification based on analog reasoning
Expert Systems with Applications: An International Journal
An efficient probabilistic framework for multi-dimensional classification
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Multilabel Learning via Random Label Selection for Protein Subcellular Multilocations Prediction
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
A unified view of class-selection with probabilistic classifiers
Pattern Recognition
Dependent binary relevance models for multi-label classification
Pattern Recognition
A Framework to Generate Synthetic Multi-label Datasets
Electronic Notes in Theoretical Computer Science (ENTCS)
Multi-label learning under feature extraction budgets
Pattern Recognition Letters
Fundamenta Informaticae - Concurrency, Specification and Programming
Irrelevant attributes and imbalanced classes in multi-label text-categorization domains
Intelligent Data Analysis
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The biological sciences are undergoing an explosion in the amount of available data. New data analysis methods are needed to deal with the data. We present work using KDD to analyse data from mutant phenotype growth experiments with the yeast S. cerevisiae to predict novel gene functions. The analysis of the data presented a number of challenges: multi-class labels, a large number of sparsely populated classes, the need to learn a set of accurate rules (not a complete classification), and a very large amount of missing values. We developed resampling strategies and modified the algorithm C4.5 to deal with these problems. Rules were learnt which are accurate and biologically meaningful. The rules predict function of 83 putative genes of currently unknown function at an estimated accuracy of ≥ 80%.