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Decision trees for hierarchical multi-label classification

Machine learning, 2008-11, Vol.73 (2), p.185-214

2008

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Predicting gene function using hierarchical multi-label decision tree ensembles

BMC bioinformatics, 2010-01, Vol.11 (1), p.2-2, Article 2

2010

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Combining gene expression, demographic and clinical data in modeling disease: a case study of bipolar disorder and schizophrenia

BMC genomics, 2008-11, Vol.9 (1), p.531-531

2008

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Tree ensembles for predicting structured outputs

Pattern recognition, 2013-03, Vol.46 (3), p.817-833

2013

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Constraint Based Induction of Multi-objective Regression Trees

Knowledge Discovery in Inductive Databases, 2006, p.222-233

2006

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Finding explained groups of time-course gene expression profiles with predictive clustering trees

Molecular bioSystems, 2010-01, Vol.6 (4), p.729-740

2010

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Knowledge discovery in inductive databases: 5th international workshop, KDID 2006, Berlin, Germany September 18, 2006

2007

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Ensembles of Multi-Objective Decision Trees

Machine Learning: ECML 2007, p.624-631

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Decision Trees for Hierarchical Multilabel Classification: A Case Study in Functional Genomics

Knowledge Discovery in Databases: PKDD 2006, 2006, p.18-29

2006

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Towards a General Framework for Data Mining

Knowledge Discovery in Inductive Databases, p.259-300

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Value, Cost, and Sharing: Open Issues in Constrained Clustering

Knowledge Discovery in Inductive Databases, p.1-10

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Using multi-objective classification to model communities of soil microarthropods

Ecological modelling, 2006-01, Vol.191 (1), p.131-143

2006

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Analysis of Time Series Data with Predictive Clustering Trees

Knowledge Discovery in Inductive Databases, p.63-80

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Knowledge Discovery in Inductive Databases: 5th International Workshop, KDID 2006 Berlin, Germany, September 18th, 2006 Revised Selected and Invited Papers

1, 2007

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Efficient Mining Under Rich Constraints Derived from Various Datasets

Knowledge Discovery in Inductive Databases, p.223-239

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Beam Search Induction and Similarity Constraints for Predictive Clustering Trees

Knowledge Discovery in Inductive Databases, p.134-151

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Integrating Decision Tree Learning into Inductive Databases

Knowledge Discovery in Inductive Databases, p.81-96

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On Interactive Pattern Mining from Relational Databases

Knowledge Discovery in Inductive Databases, p.42-62

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IQL: A Proposal for an Inductive Query Language

Knowledge Discovery in Inductive Databases, p.189-207

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Frequent Pattern Mining and Knowledge Indexing Based on Zero-Suppressed BDDs

Knowledge Discovery in Inductive Databases, p.152-169

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Three Strategies for Concurrent Processing of Frequent Itemset Queries Using FP-Growth

Knowledge Discovery in Inductive Databases, p.240-258

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Query Transformations for Improving the Efficiency of ILP Systems

Journal of machine learning research, 2004-05, Vol.4 (4), p.465-491

2004

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Extending the Soft Constraint Based Mining Paradigm

Knowledge Discovery in Inductive Databases, p.24-41

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Learning Predictive Clustering Rules

Knowledge Discovery in Inductive Databases, 2006, p.234-250

2006

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An Efficient Approximation to Lookahead in Relational Learners

Lecture notes in computer science, 2006, p.775-782

2006

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Decision trees for hierarchical multi-label classification

Predicting gene function using hierarchical multi-label decision tree ensembles

Combining gene expression, demographic and clinical data in modeling disease: a case study of bipolar disorder and schizophrenia

Tree ensembles for predicting structured outputs

Constraint Based Induction of Multi-objective Regression Trees

Finding explained groups of time-course gene expression profiles with predictive clustering trees

Knowledge discovery in inductive databases: 5th international workshop, KDID 2006, Berlin, Germany September 18, 2006

Ensembles of Multi-Objective Decision Trees

Decision Trees for Hierarchical Multilabel Classification: A Case Study in Functional Genomics

Towards a General Framework for Data Mining

Value, Cost, and Sharing: Open Issues in Constrained Clustering

Using multi-objective classification to model communities of soil microarthropods

Analysis of Time Series Data with Predictive Clustering Trees

Knowledge Discovery in Inductive Databases: 5th International Workshop, KDID 2006 Berlin, Germany, September 18th, 2006 Revised Selected and Invited Papers

Efficient Mining Under Rich Constraints Derived from Various Datasets

Beam Search Induction and Similarity Constraints for Predictive Clustering Trees

Integrating Decision Tree Learning into Inductive Databases

On Interactive Pattern Mining from Relational Databases

IQL: A Proposal for an Inductive Query Language

Frequent Pattern Mining and Knowledge Indexing Based on Zero-Suppressed BDDs

Three Strategies for Concurrent Processing of Frequent Itemset Queries Using FP-Growth

Query Transformations for Improving the Efficiency of ILP Systems

Extending the Soft Constraint Based Mining Paradigm

Learning Predictive Clustering Rules

An Efficient Approximation to Lookahead in Relational Learners

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