Saso Dzeroski

Saso Dzeroski, Nikola Simidjievski, Pance Panov, 2019, 2019 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO).

Combining model-based and instance-based learning for first order regression

Saso Dzeroski, Kurt Driessens, K. Driessens, 2005, BNAIC.

Inductive Queries on Polynomial Equations

Saso Dzeroski, Ljupco Todorovski, Peter Ljubic, 2004, Constraint-Based Mining and Inductive Databases.

Machine Learning for Predicting Thermal Power Consumption of the Mars Express Spacecraft

Bernard Zenko, Saso Dzeroski, Nikola Simidjievski, 2018, IEEE Aerospace and Electronic Systems Magazine.

Integrating Knowledge-Driven and Data-Driven Approaches to Modeling

Saso Dzeroski, Ljupco Todorovski, S. Džeroski, 2006, EnviroInfo.

Multi-label classification via multi-target regression on data streams

Saso Dzeroski, Pance Panov, Aljaz Osojnik, 2015, Machine Learning.

Using ILP to study the presence of genetically modified variants in organic oil seed rape

Saso Dzeroski, Celine Vens, Aneta Ivanovska, 2006 .

Morphosyntactic Tagging of Slovene Using Progol

Saso Dzeroski, Tomaz Erjavec, James Cussens, 1999, ILP.

Modelling The Growth Of AlgaeIn The Lagoon Of VeniceWith The Artificial Intelligence Tool GoldHorn

Saso Dzeroski, Boris Kompare, Viljem Krizman, 1997 .

Global and Local Spatial Autocorrelation in Predictive Clustering Trees

Michelangelo Ceci, Donato Malerba, Saso Dzeroski, 2011, Discovery Science.

Diterpene Structure Elucidation from 13CNMR Spectra with Inductive Logic Programming

Saso Dzeroski, Hendrik Blockeel, Steffen Schulze-Kremer, 1998, Appl. Artif. Intell..

Phyletic Profiling with Cliques of Orthologs Is Enhanced by Signatures of Paralogy Relationships

Saso Dzeroski, Tomislav Smuc, Pance Panov, 2013, PLoS Comput. Biol..

Predicting Aggregate Properties of Soil Communities vs. Community Structure in an Agricultural Setting

Saso Dzeroski, Marko Debeljak, Damjan Demsar, 2006, EnviroInfo.

Using Decision Trees to Predict Forest Stand Height and Canopy Cover from LANDSAT and LIDAR Data

Saso Dzeroski, Pance Panov, Andrej Kobler, 2006, EnviroInfo.

Inductive Databases and Constraint-Based Data Mining

Saso Dzeroski, S. Džeroski, 2011, ICFCA.

Extending Redescription Mining to Multiple Views

Saso Dzeroski, Matej Mihelcic, Tomislav Smuc, 2018, DS.

Probabilistic Grammars for Equation Discovery pdf

Saso Dzeroski, Ljupco Todorovski, Jure Brence, 2020, Knowl. Based Syst..

Image Representation, Annotation and Retrieval with Predictive Clustering Trees

Saso Dzeroski, Ivica Dimitrovski, Suzana Loskovska, 2017, ECML/PKDD.

Acquiring and Validating Background Knowledge for Machine Learning Using Function Decomposition

Saso Dzeroski, Blaz Zupan, S. Džeroski, 1997, AIME.

Stacking with an Extended Set of Meta-level Attributes and MLR

Bernard Zenko, Saso Dzeroski, S. Džeroski, 2002, ECML.

Multi-relational data mining 2004: workshop report

Saso Dzeroski, Hendrik Blockeel, 2004, SKDD.

Semi-supervised learning for multi-target regression (Discussion paper)

Michelangelo Ceci, Saso Dzeroski, Dragi Kocev, 2015, SEBD.

Semi-supervised classification trees

Michelangelo Ceci, Saso Dzeroski, Dragi Kocev, 2017, Journal of Intelligent Information Systems.

Feature ranking for semi-supervised learning pdf

Saso Dzeroski, Dragi Kocev, Matej Petkovic, 2020, Machine Learning.

Using Constraints in Discovering Dynamics

Saso Dzeroski, Ljupco Todorovski, Peter Ljubic, 2003, Discovery Science.

Knowledge Discovery in a Water Quality Database

Saso Dzeroski, 1995, KDD.

Multi-Attribute Modelling of Economic and Ecological Impacts of Cropping Systems

Saso Dzeroski, Marko Bohanec, Martin Znidarsic, 2004, Informatica.

Morphosyntactic Tagging of Slovene: Evaluating Taggers and Tagsets

Jakub Zavrel, Saso Dzeroski, Tomaz Erjavec, 2000, LREC.

Itemset Support Queries Using Frequent Itemsets and Their Condensed Representations

Saso Dzeroski, Taneli Mielikäinen, Pance Panov, 2006, Discovery Science.

The utility of background knowledge in learning medical diagnostic rules

Saso Dzeroski, Nada Lavrac, Vladimir Pirnat, 1993, Appl. Artif. Intell..

Ranking with Predictive Clustering Trees

Saso Dzeroski, Hendrik Blockeel, Ljupco Todorovski, 2002, ECML.

Using Domain Specific Knowledge for Automated Modeling

Saso Dzeroski, Ljupco Todorovski, S. Džeroski, 2003, IDA.

Network regression with predictive clustering trees

Michelangelo Ceci, Saso Dzeroski, Annalisa Appice, 2011, Data Mining and Knowledge Discovery.

Inductive Databases of Polynomial Equations

Saso Dzeroski, Ljupco Todorovski, Peter Ljubic, 2004, KDID.

Clustering trees with instance level constraints (Extended abstract)

Saso Dzeroski, Jan Struyf, 2007 .

Automated Revision of Expert Rules for Treating Acute Abdominal Pain in Children

Saso Dzeroski, George Potamias, Vassilis Moustakis, 1997, AIME.

Predicting Structured Outputs k-Nearest Neighbours Method

Saso Dzeroski, Mitja Pugelj, S. Džeroski, 2011, Discovery Science.

ReliefF for Hierarchical Multi-label Classification

Saso Dzeroski, Slobodan Kalajdziski, Dragi Kocev, 2013, NFMCP.

PAC-learnability of determinate logic programs

Saso Dzeroski, Stephen Muggleton, Stuart J. Russell, 1992, COLT '92.

Improving bag-of-visual-words image retrieval with predictive clustering trees

Saso Dzeroski, Ivica Dimitrovski, Suzana Loskovska, 2016, Inf. Sci..

Learning to Lemmatise Slovene Words

Saso Dzeroski, Tomaz Erjavec, S. Džeroski, 2001, Learning Language in Logic.

Hierarchical classification of diatom images using ensembles of predictive clustering trees

Saso Dzeroski, Ivica Dimitrovski, Suzana Loskovska, 2012, Ecol. Informatics.

Local Patterns: Theory and Practice of Constraint-Based Relational Subgroup Discovery

Saso Dzeroski, Nada Lavrac, Filip Zelezný, 2004, Local Pattern Detection.

Inductive Logic Programming: Techniques and Applications

Saso Dzeroski, Nada Lavrac, S. Džeroski, 1993 .

Declarative Bias in Equation Discovery

Saso Dzeroski, Ljupco Todorovski, S. Džeroski, 1997, ICML.

Ensembles of Multi-Objective Decision Trees

Saso Dzeroski, Celine Vens, Jan Struyf, 2007, ECML.

The Use of the Label Hierarchy in Hierarchical Multi-label Classification Improves Performance

Saso Dzeroski, Dragi Kocev, Jurica Levatic, 2013, NFMCP.

Applying ILP to Diterpene Structure Elucidation from 13C NMR Spectra

Saso Dzeroski, Steffen Schulze-Kremer, Karsten R. Heidtke, 1996, Inductive Logic Programming Workshop.

Handling Real Numbers in ILP: A Step Towards Better Behavioural Clones (Extended Abstract)

Saso Dzeroski, Ljupco Todorovski, Tanja Urbancic, 1995, ECML.

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

Saso Dzeroski, Jan Struyf, Ivica Slavkov, 2010, Molecular bioSystems.

Proceedings of the Ninth International Workshop on Inductive Logic Programming (ILP'99)

Peter A. Flach, Saso Dzeroski, S. Džeroski, 1999 .

Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis

Saso Dzeroski, Ljupco Todorovski, Jurij Silc, 2011, BMC Systems Biology.

Self-training for multi-target regression with tree ensembles

Michelangelo Ceci, Saso Dzeroski, Dragi Kocev, 2017, Knowl. Based Syst..

Detection of Visual Concepts and Annotation of Images Using Predictive Clustering Trees

Saso Dzeroski, Ivica Dimitrovski, Suzana Loskovska, 2010, CLEF.

Hybrid Decision Tree Architecture Utilizing Local SVMs for Efficient Multi-Label Learning

Saso Dzeroski, Dejan Gjorgjevikj, Gjorgji Madjarov, 2013, Int. J. Pattern Recognit. Artif. Intell..

Modeling dynamical systems with data stream mining

Saso Dzeroski, Pance Panov, Aljaz Osojnik, 2016, Comput. Sci. Inf. Syst..

Using Simulation Models and Data Mining to Study Co-Existence of GM/Non-GM Crops at Regional Level

Saso Dzeroski, Antoine Messéan, Aneta Ivanovska, 2006, EnviroInfo.

Predicting Gene Function using Predictive Clustering Trees

Saso Dzeroski, Celine Vens, Hendrik Blockeel, 2010, Inductive Databases and Constraint-Based Data Mining.

Acquiring background knowledge for machine learning using function decomposition: a case study in rheumatology

Saso Dzeroski, Blaz Zupan, 1998, Artif. Intell. Medicine.

First-Order jk-Clausal Theories are PAC-Learnable

Luc De Raedt, Saso Dzeroski, L. D. Raedt, 1994, Artif. Intell..

Random forests for combining selection and aggregation in relational data mining

Saso Dzeroski, Celine Vens, Hendrik Blockeel, 2004 .

On using guidance in relational reinforcement learning

Saso Dzeroski, Kurt Driessens, 2002 .

Proceedings of the 7th International Workshop on Inductive Logic Programming

Saso Dzeroski, Nada Lavrač, 1997 .

Learning from Massive, Incompletely annotated & Structured Data

Saso Dzeroski, 2016, EGC.

Detection of Visual Concepts and Annotation of Images Using Ensembles of Trees for Hierarchical Multi-Label Classification

Saso Dzeroski, Ivica Dimitrovski, Suzana Loskovska, 2010, ICPR Contests.

Induction of Slovene Nominal Paradigms

Saso Dzeroski, Tomaz Erjavec, 1997, ILP.

Learning Nonrecursive Definitions of Relations with LINUS

Saso Dzeroski, Marko Grobelnik, Nada Lavrac, 1991, EWSL.

Online tree-based ensembles and option trees for regression on evolving data streams

Saso Dzeroski, João Gama, Elena Ikonomovska, 2015, Neurocomputing.

Inducing Multi-Target Model Trees in a Stepwise Fashion

Saso Dzeroski, Annalisa Appice, 2007, SEBD.

Estimating vegetation height and canopy cover from remotely sensed data with machine learning

Saso Dzeroski, Daniela Stojanova, Pance Panov, 2010, Ecol. Informatics.

Hierarchical annotation of medical images

Saso Dzeroski, Ivica Dimitrovski, Suzana Loskovska, 2011, Pattern Recognit..

Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27 - 30, 1999

Ivan Bratko, Saso Dzeroski, I. Bratko, 1999, ICML.

Evaluation Method for Feature Rankings and their Aggregations for Biomarker Discovery

Bernard Zenko, Saso Dzeroski, Ivica Slavkov, 2009, MLSB.

Speeding-Up Hoeffding-Based Regression Trees With Options

Bernard Zenko, Saso Dzeroski, João Gama, 2011, ICML.

EXPERIMENTS IN PREDICTING BIODEGRADABILITY

Saso Dzeroski, Wim Van Laer, Hendrik Blockeel, 1999, ILP.

Semi-supervised trees for multi-target regression

Michelangelo Ceci, Saso Dzeroski, Dragi Kocev, 2018, Inf. Sci..

The Monk''s Problem''s: A Performance Comparison of Different Learning Methods

Ivan Bratko, Peter W. Pachowicz, Sebastian Thrun, 1991 .

Theory Revision in Equation Discovery

Saso Dzeroski, Ljupco Todorovski, S. Džeroski, 2001, Discovery Science.

Using data mining and OLAP to discover patterns in a database of patients with Y-chromosome deletions

Saso Dzeroski, Borut Peterlin, Dimitar Hristovski, 2000, AMIA.

Proceedings of the 4th international workshop on Multi-relational mining

Saso Dzeroski, Hendrik Blockeel, 2005 .

Constrained Predictive Clustering

Saso Dzeroski, Jan Struyf, 2010, Inductive Databases and Constraint-Based Data Mining.

Integrating Domain Knowledge in Equation Discovery

Saso Dzeroski, Ljupco Todorovski, S. Džeroski, 2007, Computational Discovery of Scientific Knowledge.

Experiments In Learning Nonrecursive Definitions Of Relations With Linus

Saso Dzeroski, Marko Grobelnik, Nada Lavrač, 1991 .

Model Tree Ensembles for the Identification of Multiple-Output Systems

Saso Dzeroski, Jus Kocijan, Darko Aleksovski, 2014, 2014 European Control Conference (ECC).

Analyzing Gene Expression Data with Predictive Clustering Trees

Saso Dzeroski, Ivica Slavkov, S. Džeroski, 2010, Inductive Databases and Constraint-Based Data Mining.

Relational Reinforcement Learning

Luc De Raedt, Saso Dzeroski, Hendrik Blockeel, 1998, ILP.

Fast and Scalable Image Retrieval Using Predictive Clustering Trees

Saso Dzeroski, Ivica Dimitrovski, Suzana Loskovska, 2013, Discovery Science.

Inductive Logic Programming and Knowledge Discovery in Databases

Saso Dzeroski, S. Džeroski, 1996, Advances in Knowledge Discovery and Data Mining.

Feature Ranking for Multi-target Regression with Tree Ensemble Methods

Saso Dzeroski, Dragi Kocev, Matej Petkovic, 2017, DS.

Integrating Experimentation and Guidance in Relational Reinforcement Learning

Saso Dzeroski, Kurt Driessens, K. Driessens, 2002, ICML.

Ensembles of Fuzzy Linear Model Trees for the Identification of Multioutput Systems

Saso Dzeroski, Jus Kocijan, Darko Aleksovski, 2016, IEEE Transactions on Fuzzy Systems.

Engineering applications of ILP

Ivan Bratko, Saso Dzeroski, I. Bratko, 1995, New Generation Computing.

Stacking with Multi-response Model Trees

Bernard Zenko, Saso Dzeroski, S. Džeroski, 2002, Multiple Classifier Systems.

Semi-supervised Learning for Multi-target Regression

Michelangelo Ceci, Saso Dzeroski, Dragi Kocev, 2014, NFMCP.

Redescription mining augmented with random forest of multi-target predictive clustering trees

Saso Dzeroski, Nada Lavrac, Matej Mihelcic, 2017, Journal of Intelligent Information Systems.

Literature Based Discovery Support System and Its Application to Disease Gene Identification

Saso Dzeroski, Borut Peterlin, Dimitar Hristovski, 2007, Computational Discovery of Scientific Knowledge.

Ensembles for multi-target regression with random output selections

Saso Dzeroski, Martin Breskvar, Dragi Kocev, 2018, Machine Learning.

Proceedings of the 22nd international conference on Machine learning

Luc De Raedt, Saso Dzeroski, Stefan Wrobel, 2005 .

Ninth International Workshop on Inductive Logic Programming (ILP'99)

Peter A. Flach, Saso Dzeroski, Blaz Zupan, 1999 .

Inductive logic programming for relational knowledge discovery

Masayuki Numao, Saso Dzeroski, Nada Lavrac, 1998, New Generation Computing.

Incremental predictive clustering trees for online semi-supervised multi-target regression

Saso Dzeroski, Pance Panov, Aljaz Osojnik, 2020, Machine Learning.

Ensemble‐ and distance‐based feature ranking for unsupervised learning pdf

Saso Dzeroski, Blaz Skrlj, Dragi Kocev, 2020, Int. J. Intell. Syst..

Handling Imperfetc Data in Inductive Logic Programming

Saso Dzeroski, 1993, SCAI.

Predicting chemical parameters of the water from diatom abudance in lake Prespa and its tributaries

Saso Dzeroski, Dragi Kocev, Andreja Naumoski, 2009, ITEE.

Semi-Supervised Multi-View Learning for Gene Network Reconstruction

Michelangelo Ceci, Saso Dzeroski, Gianvito Pio, 2015, SEBD.

Predictive Clustering of Multi-dimensional Time Series Applied to Forest Growing Stock Data for Different Tree Sizes

Saso Dzeroski, Marko Debeljak, Dragi Kocev, 2017, ICT Innovations.

Supporting Discovery in Medicine by Association Rule Mining in Medline and UMLS

Saso Dzeroski, Borut Peterlin, Dimitar Hristovski, 2001, MedInfo.

Semi-Supervised Learning for Quantitative Structure-Activity Modeling

Saso Dzeroski, Tomislav Smuc, Fran Supek, 2013, Informatica.

Feature Ranking with Relief for Multi-label Classification: Does Distance Matter?

Saso Dzeroski, Dragi Kocev, Matej Petkovic, 2018, DS.

Automated discovery of a model for dinoflagellate dynamics

Saso Dzeroski, Ljupco Todorovski, Boris Kompare, 2011, Environ. Model. Softw..

Generic ontology of datatypes

Saso Dzeroski, Larisa N. Soldatova, Pance Panov, 2016, Inf. Sci..

Dealing with spatial autocorrelation when learning predictive clustering trees

Michelangelo Ceci, Donato Malerba, Saso Dzeroski, 2013, Ecol. Informatics.

Ensemble-Based Feature Ranking for Semi-supervised Classification

Saso Dzeroski, Dragi Kocev, Matej Petkovic, 2019, DS.

Combining Multiple Models with Meta Decision Trees

Saso Dzeroski, Ljupco Todorovski, 2000, PKDD.

Representing bioinformatics datatypes using the OntoDT ontology

Saso Dzeroski, Larisa N. Soldatova, Pance Panov, 2015, ICBO.

Proceedings of the 2nd International Workshop on Knowledge Discovery in Inductive Databases (KDID-2003)

Saso Dzeroski, Jean-François Boulicaut, S. Džeroski, 2003 .

A comparison of stacking with meta decision trees to bagging, boosting, and stacking with other methods

Bernard Zenko, Saso Dzeroski, Ljupco Todorovski, 2001, Proceedings 2001 IEEE International Conference on Data Mining.

Editorial: Inductive Logic Programming is Coming of Age

Peter A. Flach, Saso Dzeroski, 2004, Machine Learning.

On Multi-class Problems and Discretization in Inductive Logic Programming

Luc De Raedt, Saso Dzeroski, Wim Van Laer, 1997, ISMIS.

Relational Data Mining

Saso Dzeroski, 2005, Data Mining and Knowledge Discovery Handbook.

General Meta-Model Framework for Surrogate-Based Numerical Optimization

Saso Dzeroski, Jovan Tanevski, Ljupco Todorovski, 2017, DS.

Regression on evolving multi-relational data streams

Saso Dzeroski, Elena Ikonomovska, S. Džeroski, 2011, PhD '11.

Automated Modeling Of Phytoplankton GrowthUsing Ecological Domain Knowledge

Saso Dzeroski, Boris Kompare, Ljupčo Todorovski, 1997 .

Using Domain Knowledge on Population Dynamics Modeling for Equation Discovery

Saso Dzeroski, Ljupco Todorovski, S. Džeroski, 2001, ECML.

Two stage architecture for multi-label learning

Saso Dzeroski, Dejan Gjorgjevikj, Gjorgji Madjarov, 2012, Pattern Recognit..

Multi-target regression with rule ensembles

Tapio Elomaa, Timo Aho, Bernard Zenko, 2012, J. Mach. Learn. Res..

Network Regression with Predictive Clustering Trees

Michelangelo Ceci, Saso Dzeroski, Annalisa Appice, 2011, ECML/PKDD.

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

Saso Dzeroski, Hendrik Blockeel, Amanda Clare, 2006, PKDD.

Machine Learning, Ensemble Methods in

Bernard Zenko, Saso Dzeroski, Pance Panov, 2009, Encyclopedia of Complexity and Systems Science.

ILPNET Repositories on WWW: Inductive Logic Programming Systems, Datasets and Bibliography

Saso Dzeroski, Nada Lavrac, Olga Stepánková, 1996, AI Commun..

A reply to Pazzani's book review of “Inductive Logic Programming: Techniques and Applications”

Saso Dzeroski, Nada Lavrac, 2004, Machine Learning.

Habitat modeling with single- and multi-target trees and ensembles

Saso Dzeroski, Dragi Kocev, S. Džeroski, 2013, Ecol. Informatics.

Beam Search Induction and Similarity Constraints for Predictive Clustering Trees

Saso Dzeroski, Jan Struyf, Dragi Kocev, 2006, KDID.

DEPARTMENT OF INTELLIGENT SYSTEMS

Saso Dzeroski, Tomaz Erjavec, S. Džeroski, 2019 .

ImageCLEF 2009 Medical Image Annotation Task: PCTs for Hierarchical Multi-Label Classification

Saso Dzeroski, Ivica Dimitrovski, Suzana Loskovska, 2009, CLEF.

Tree-based methods for online multi-target regression

Saso Dzeroski, Pance Panov, Aljaz Osojnik, 2018, Journal of Intelligent Information Systems.

Phenotype Prediction with Semi-supervised Classification Trees

Saso Dzeroski, Dragi Kocev, Tomislav Smuc, 2017, NFMCP@PKDD/ECML.

Learning Multilingual Morphology with CLOG

Saso Dzeroski, Tomaz Erjavec, Suresh Manandhar, 1998, ILP.

Discovering Dynamics

Saso Dzeroski, Ljupco Todorovski, S. Džeroski, 1993, ICML.

Hierarchy Decomposition Pipeline: A Toolbox for Comparison of Model Induction Algorithms on Hierarchical Multi-label Classification Problems

Saso Dzeroski, Vedrana Vidulin, S. Džeroski, 2020, DS.

Learning model trees from evolving data streams

Saso Dzeroski, João Gama, Elena Ikonomovska, 2010, Data Mining and Knowledge Discovery.

Weakening the language bias in LINUS

Saso Dzeroski, Nada Lavrac, S. Džeroski, 1994, J. Exp. Theor. Artif. Intell..

A Minimal Description Length Scheme for Polynomial Regression

Saso Dzeroski, Ljupco Todorovski, Aleksandar Peckov, 2008, PAKDD.

Tree ensembles for predicting structured outputs

Saso Dzeroski, Celine Vens, Jan Struyf, 2013, Pattern Recognit..

Combining Classifiers with Meta Decision Trees

Saso Dzeroski, Ljupco Todorovski, S. Džeroski, 2003, Machine Learning.

An Algorithm, Implementation and Execution Ontology Design Pattern

Saso Dzeroski, Joaquin Vanschoren, Diego Esteves, 2016, WOP@ISWC.

Multi-relational data mining: the current frontiers

Luc De Raedt, Saso Dzeroski, 2003, SKDD.

A report on the fourth international workshop on environmental applications of machine learning (EAML 2004)

Bernard Zenko, Saso Dzeroski, Marko Debeljak, 2004, SKDD.

Hierarchical multilabel classification trees for gene function prediction (Extended abstract)

Saso Dzeroski, Hendrik Blockeel, Amanda Clare, 2006 .

Multi-relational data mining: a workshop report

Luc De Raedt, Saso Dzeroski, 2002, SKDD.

Multi-label classification via multi-target regression on data streams

Saso Dzeroski, Pance Panov, Aljaz Osojnik, 2016, Machine Learning.

Towards a General Framework for Data Mining

Saso Dzeroski, S. Džeroski, 2006, KDID.

Inductive Learning in Deductive Databases

Saso Dzeroski, Nada Lavrac, S. Džeroski, 1993, IEEE Trans. Knowl. Data Eng..

Predictive Clustering Trees for Hierarchical Multi-Target Regression

Saso Dzeroski, Dragi Kocev, Vanja Mileski, 2017, IDA.

Multi-relational data mining: an introduction

Saso Dzeroski, S. Džeroski, 2003, SKDD.

The ILP description learning problem: Towards a general model-level definition of data mining in ILP

Saso Dzeroski, Stefan Wrobel, Schlo Birlinghoven, 1995 .

OntoDM-KDD: Ontology for Representing the Knowledge Discovery Process

Saso Dzeroski, Larisa N. Soldatova, Pance Panov, 2013, Discovery Science.

Constraint Based Induction of Multi-objective Regression Trees

Saso Dzeroski, Jan Struyf, S. Džeroski, 2005, KDID.

Model-Tree Ensembles for noise-tolerant system identification

Saso Dzeroski, Jus Kocijan, Darko Aleksovski, 2015, Adv. Eng. Informatics.

Computational Discovery of Communicable Knowledge: Symposium Report

Saso Dzeroski, Pat Langley, P. Langley, 2001, Discovery Science.

Estimating the Importance of Relational Features by Using Gradient Boosting

Michelangelo Ceci, Kristian Kersting, Saso Dzeroski, 2020, ISMIS.

Incremental multi-target model trees for data streams

Saso Dzeroski, João Gama, Elena Ikonomovska, 2011, SAC.

Ontology Engineering: From an Art to a Craft - The Case of the Data Mining Ontologies

Saso Dzeroski, Larisa N. Soldatova, Pance Panov, 2015, OWLED.

Background Knowledge and Declarative Bias in Inductive Concept Learning

Saso Dzeroski, Nada Lavrac, S. Džeroski, 1992, AII.

Combining Bagging and Random Subspaces to Create Better Ensembles

Saso Dzeroski, Pance Panov, S. Džeroski, 2007, IDA.

Aggregation and selection in relational data mining

Saso Dzeroski, Celine Vens, Hendrik Blockeel, 2004 .

Multiple Predicate Learning

Luc De Raedt, Saso Dzeroski, Nada Lavrac, 1993, IJCAI.

First Order Random Forests with Complex Aggregates

Saso Dzeroski, Celine Vens, Hendrik Blockeel, 2004, ILP.

Learning Ensembles of Process-Based Models by Bagging of Random Library Samples

Saso Dzeroski, Nikola Simidjievski, Ljupco Todorovski, 2016, DS.

A Comparison of Different Data Transformation Approaches in the Feature Ranking Context

Saso Dzeroski, Pance Panov, Matej Petkovic, 2016, DS.

Integrating Explanatory and Descriptive Learning in ILP

Saso Dzeroski, Antonis C. Kakas, Yannis Dimopoulos, 1997, IJCAI.

Inductive Logic Programming : 9th International Workshop, ILP-99, Bled, Slovenia, June 1999 : Proceedings

Peter A. Flach, Saso Dzeroski, 1999 .

Learning First-order Clausal Theories in the Presence of Noise

Saso Dzeroski, S. Džeroski, 1995, Scandinavian Conference on AI.

Decision trees for hierarchical multi-label classification

Saso Dzeroski, Celine Vens, Hendrik Blockeel, 2008, Machine Learning.

Multirelational data mining 2003: workshop report

Luc De Raedt, Saso Dzeroski, Stefan Wrobel, 2003, SKDD.

Predicting Thermal Power Consumption of the Mars Express Satellite with Data Stream Mining

Saso Dzeroski, Ivica Dimitrovski, Dragi Kocev, 2019, DS.

Utilizing Hierarchies in Tree-Based Online Structured Output Prediction

Saso Dzeroski, Pance Panov, Aljaz Osojnik, 2019, DS.

OntoDM: An Ontology of Data Mining

Saso Dzeroski, Larisa N. Soldatova, Pance Panov, 2008, 2008 IEEE International Conference on Data Mining Workshops.

Clustering Trees with Instance Level Constraints

Saso Dzeroski, Jan Struyf, S. Džeroski, 2007, ECML.

Noise Elimination in Inductive Concept Learning: A Case Study in Medical Diagnosois

Saso Dzeroski, Nada Lavrac, Dragan Gamberger, 1996, ALT.

Proceedings of the Second International Workshop on Inductive Databases, 22 September, Cavtat-Dubrovnik, Croatia

Jean-François Boulicaut, Saso Dzeroski, 2003, KDID.

Relational ranking with predictive clustering trees

Saso Dzeroski, Hendrik Blockeel, Ljupčo Todorovski, 2002 .

A framework for redescription set construction

Saso Dzeroski, Nada Lavrac, Matej Mihelcic, 2017, Expert Syst. Appl..

Modelling Soil Radon Concentration for Earthquake Prediction

Saso Dzeroski, Ljupco Todorovski, Ivan Kobal, 2003, Discovery Science.

Discovering dynamics: From inductive logic programming to machine discovery

Saso Dzeroski, Ljupco Todorovski, S. Džeroski, 1993, Journal of Intelligent Information Systems.

Experiments in Predicting Biodegradability

Saso Dzeroski, Wim Van Laer, Hendrik Blockeel, 1999, ILP.

Equation Discovery for Nonlinear System Identification

Saso Dzeroski, Nikola Simidjievski, Ljupco Todorovski, 2019, IEEE Access.

Proceedings of the Second International Workshop on Inductive Databases

Jean-François Boulicaut, Saso Dzeroski, 2003 .

Learning Hierarchical Multi-label Classification Trees from Network Data

Michelangelo Ceci, Donato Malerba, Saso Dzeroski, 2013, Discovery Science.

Identification Of The Lake Of Bled EcosystemWith The Artificial Intelligence Tools M5 And FORS

Saso Dzeroski, Boris Kompare, Aram Karalic, 1997 .

Towards a Slovene Dependency Treebank

Saso Dzeroski, Tomaz Erjavec, Petr Pajas, 2006, LREC.

Using redescription mining to relate clinical and biological characteristics of cognitively impaired and Alzheimer’s disease patients

Saso Dzeroski, Nada Lavrac, Matej Mihelcic, 2017, PloS one.

Knowledge discovery by means of inductive methods in wastewater treatment plannt data

Miquel Sànchez-Marrè, Saso Dzeroski, Karina Gibert, 2001, AI Commun..

Computational Discovery of Scientific Knowledge

Saso Dzeroski, Pat Langley, Ljupco Todorovski, 2007, Computational Discovery of Scientific Knowledge.

Is Combining Classifiers with Stacking Better than Selecting the Best One?

Bernard Zenko, Saso Dzeroski, S. Džeroski, 2004, Machine Learning.

Option Predictive Clustering Trees for Multi-target Regression

Saso Dzeroski, Dragi Kocev, Aljaz Osojnik, 2016, DS.

First order random forests: Learning relational classifiers with complex aggregates

Saso Dzeroski, Celine Vens, Hendrik Blockeel, 2006, Machine Learning.

Inductive process modeling

Saso Dzeroski, Pat Langley, Ljupco Todorovski, 2008, Machine Learning.

Integrating Guidance into Relational Reinforcement Learning

Saso Dzeroski, Kurt Driessens, K. Driessens, 2004, Machine Learning.

An extensive experimental comparison of methods for multi-label learning

Saso Dzeroski, Dejan Gjorgjevikj, Gjorgji Madjarov, 2012, Pattern Recognit..

Analysis of Time Series Data with Predictive Clustering Trees

Saso Dzeroski, Jan Struyf, Ivica Slavkov, 2006, KDID.

GalaxAI: Machine learning toolbox for interpretable analysis of spacecraft telemetry data pdf

Saso Dzeroski, Nikola Simidjievski, Dragi Kocev, 2021, ArXiv.

Explaining the performance of multilabel classification methods with data set properties pdf

Saso Dzeroski, Ljupco Todorovski, Dragi Kocev, 2021, Int. J. Intell. Syst..

OPTION: OPTImization Algorithm Benchmarking ONtology

Saso Dzeroski, Tome Eftimov, Carola Doerr, 2021, IEEE Transactions on Evolutionary Computation.

Using Machine Learning to Identify Factors Contributing to Mould in the Celje Ceiling Painting

Saso Dzeroski, Stefan Popov, Katja Kavkler, 2021, 2021 44th International Convention on Information, Communication and Electronic Technology (MIPRO).

Relating Prenatal Hg Exposure and Neurological Development in Children with Machine Learning

Saso Dzeroski, Martin Breskvar, Stefan Popov, 2021, 2021 44th International Convention on Information, Communication and Electronic Technology (MIPRO).

Unsupervised Feature Ranking via Attribute Networks

Saso Dzeroski, Blaz Skrlj, Matej Petkovic, 2021, DS.

Comprehensive Comparative Study of Multi-Label Classification Methods pdf

Saso Dzeroski, Ljupco Todorovski, Dragi Kocev, 2021, Expert Syst. Appl..

Experiments with TILDE in the river water quality domain

Saso Dzeroski, Hendrik Blockeel, S. Džeroski, 1999 .

Inductive Logic Programming 7th International Workshop, Ilp-97, Prague, Czech Republic, September 17-20, 1997 : Proceedings

Saso Dzeroski, Nada Lavrač, 1997 .

Relating Biodiversity of River Communities to Physical and Chemical Water Properties

Saso Dzeroski, Jasna Grbovic, 2001 .

Sustainable introduction of GM crops into european agriculture: a summary report of the FP6 SIGMEA research project *

Saso Dzeroski, Broder Breckling, Antoine Messéan, 2009 .