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ORCIDSaso Dzeroski
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- affiliation: Jožef Stefan Institute, Department of Intelligent Systems
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2020 – today
- 2021
[j100]Martin Breskvar
, Saso Dzeroski:
Multi-Target Regression Rules With Random Output Selections. IEEE Access 9: 10509-10522 (2021)- [j99]Matej Petkovic, Ivica Slavkov, Dragi Kocev, Saso Dzeroski:
Biomarker discovery by feature ranking: Evaluation on a case study of embryonal tumors. Comput. Biol. Medicine 128: 104143 (2021) - [j98]Stevanche Nikoloski, Dragi Kocev, Jurica Levatic, David P. Wall, Saso Dzeroski:
Exploiting partially-labeled data in learning predictive clustering trees for multi-target regression: A case study of water quality assessment in Ireland. Ecol. Informatics 61: 101161 (2021) - [j97]Rok Piltaver, Mitja Lustrek, Saso Dzeroski, Martin Gjoreski, Matjaz Gams:
Learning comprehensible and accurate hybrid trees. Expert Syst. Appl. 164: 113980 (2021) - [j96]Jure Brence, Ljupco Todorovski, Saso Dzeroski:
Probabilistic grammars for equation discovery. Knowl. Based Syst. 224: 107077 (2021) - [i16]Blaz Skrlj, Saso Dzeroski, Nada Lavrac, Matej Petkovic:
ReliefE: Feature Ranking in High-dimensional Spaces via Manifold Embeddings. CoRR abs/2101.09577 (2021) - [i15]Jasmin Bogatinovski, Ljupco Todorovski, Saso Dzeroski, Dragi Kocev:
Comprehensive Comparative Study of Multi-Label Classification Methods. CoRR abs/2102.07113 (2021) - [i14]Ana Kostovska, Diederick Vermetten, Carola Doerr, Saso Dzeroski, Pance Panov, Tome Eftimov:
OPTION: OPTImization Algorithm Benchmarking ONtology. CoRR abs/2104.11889 (2021) - 2020
- [j95]Nikola Simidjievski, Ljupco Todorovski, Jus Kocijan, Saso Dzeroski:
Equation Discovery for Nonlinear System Identification. IEEE Access 8: 29930-29943 (2020) - [j94]Tomaz Stepisnik, Aljaz Osojnik, Saso Dzeroski, Dragi Kocev:
Option predictive clustering trees for multi-target regression. Comput. Sci. Inf. Syst. 17(2): 459-486 (2020) - [j93]Jovan Tanevski, Ljupco Todorovski, Saso Dzeroski:
Combinatorial search for selecting the structure of models of dynamical systems with equation discovery. Eng. Appl. Artif. Intell. 89: 103423 (2020) - [j92]Jurica Levatic, Michelangelo Ceci, Tomaz Stepisnik, Saso Dzeroski, Dragi Kocev:
Semi-supervised regression trees with application to QSAR modelling. Expert Syst. Appl. 158: 113569 (2020) - [j91]Matej Petkovic, Dragi Kocev, Saso Dzeroski:
Feature ranking for multi-target regression. Mach. Learn. 109(6): 1179-1204 (2020) - [j90]Aljaz Osojnik, Pance Panov, Saso Dzeroski:
Incremental predictive clustering trees for online semi-supervised multi-target regression. Mach. Learn. 109(11): 2121-2139 (2020) - [j89]Matej Petkovic, Saso Dzeroski, Dragi Kocev:
Multi-label feature ranking with ensemble methods. Mach. Learn. 109(11): 2141-2159 (2020) - [j88]Ivica Slavkov, Matej Petkovic, Pierre Geurts, Dragi Kocev, Saso Dzeroski:
Error curves for evaluating the quality of feature rankings. PeerJ Comput. Sci. 6: e310 (2020) - [j87]Maja Somrak, Saso Dzeroski, Ziga Kokalj:
Learning to Classify Structures in ALS-Derived Visualizations of Ancient Maya Settlements with CNN. Remote. Sens. 12(14): 2215 (2020) - [c158]Ilin Tolovski, Saso Dzeroski, Pance Panov:
Semantic Annotation of Predictive Modelling Experiments. DS 2020: 124-139 - [c157]Ana Kostovska, Saso Dzeroski, Pance Panov:
Semantic Description of Data Mining Datasets: An Ontology-Based Annotation Schema. DS 2020: 140-155 - [c156]Jure Brence, Jovan Tanevski, Jennifer Adams, Edward Malina, Saso Dzeroski:
Learning Surrogates of a Radiative Transfer Model for the Sentinel 5P Satellite. DS 2020: 217-230 - [c155]Vedrana Vidulin, Saso Dzeroski:
Hierarchy Decomposition Pipeline: A Toolbox for Comparison of Model Induction Algorithms on Hierarchical Multi-label Classification Problems. DS 2020: 486-501 - [c154]Blaz Skrlj, Saso Dzeroski, Nada Lavrac, Matej Petkovic:
Feature Importance Estimation with Self-Attention Networks. ECAI 2020: 1491-1498 - [c153]Matej Petkovic, Michelangelo Ceci, Kristian Kersting, Saso Dzeroski:
Estimating the Importance of Relational Features by Using Gradient Boosting. ISMIS 2020: 362-371 - [c152]Martin Breskvar, Saso Dzeroski:
Predicting Associations Between Proteins and Multiple Diseases. ISMIS 2020: 383-392 - [i13]Blaz Skrlj, Saso Dzeroski, Nada Lavrac, Matej Petkovic:
Feature Importance Estimation with Self-Attention Networks. CoRR abs/2002.04464 (2020) - [i12]Matej Mihelcic, Saso Dzeroski, Tomislav Smuc:
Multi-view redescription mining using tree-based multi-target prediction models. CoRR abs/2006.12227 (2020) - [i11]Matej Petkovic, Saso Dzeroski, Dragi Kocev:
Feature Ranking for Semi-supervised Learning. CoRR abs/2008.03937 (2020) - [i10]Matej Petkovic, Dragi Kocev, Blaz Skrlj, Saso Dzeroski:
Ensemble- and Distance-Based Feature Ranking for Unsupervised Learning. CoRR abs/2011.11679 (2020) - [i9]Jure Brence, Ljupco Todorovski, Saso Dzeroski:
Probabilistic Grammars for Equation Discovery. CoRR abs/2012.00428 (2020)
2010 – 2019
- 2019
- [j86]Franklin Parrales Bravo, Alberto A. Del Barrio García, Ana Beatriz Gago Veiga, María Mercedes Gallego de la Sacristana, Marina Ruiz Piñero, Angel Guerrero Peral, Saso Dzeroski, José L. Ayala:
SMURF: Systematic Methodology for Unveiling Relevant Factors in Retrospective Data on Chronic Disease Treatments. IEEE Access 7: 92598-92614 (2019) - [j85]Stevanche Nikoloski, Dragi Kocev, Saso Dzeroski:
Data-Driven Structuring of the Output Space Improves the Performance of Multi-Target Regressors. IEEE Access 7: 145177-145198 (2019) - [j84]Ziga Luksic, Jovan Tanevski, Saso Dzeroski, Ljupco Todorovski:
Meta-Model Framework for Surrogate-Based Parameter Estimation in Dynamical Systems. IEEE Access 7: 181829-181841 (2019) - [j83]Gjorgi Peev, Nikola Simidjievski, Saso Dzeroski:
Aiding the Task of Process-Based Modeling with ProBMoTViz. Int. J. Web Appl. 11(1): 27-38 (2019) - [c151]Aljaz Osojnik, Pance Panov, Saso Dzeroski:
Utilizing Hierarchies in Tree-Based Online Structured Output Prediction. DS 2019: 87-95 - [c150]Bozhidar Stevanoski, Dragi Kocev, Aljaz Osojnik, Ivica Dimitrovski, Saso Dzeroski:
Predicting Thermal Power Consumption of the Mars Express Satellite with Data Stream Mining. DS 2019: 186-201 - [c149]Matej Petkovic, Saso Dzeroski, Dragi Kocev:
Ensemble-Based Feature Ranking for Semi-supervised Classification. DS 2019: 290-305 - [c148]Ilin Tolovski, Ana Kostovska, Nikola Simidjievski, Ljupco Todorovski, Saso Dzeroski, Pance Panov:
Towards reusable process-based models of dynamical systems: A case study in the domain of aquatic ecosystems. MIPRO 2019: 1110-1115 - [e14]Petra Kralj Novak, Tomislav Smuc, Saso Dzeroski:
Discovery Science - 22nd International Conference, DS 2019, Split, Croatia, October 28-30, 2019, Proceedings. Lecture Notes in Computer Science 11828, Springer 2019, ISBN 978-3-030-33777-3 [contents] - [i8]Ziga Luksic, Jovan Tanevski, Saso Dzeroski, Ljupco Todorovski:
Meta-Model Framework for Surrogate-Based Parameter Estimation in Dynamical Systems. CoRR abs/1906.09088 (2019) - [i7]Nikola Simidjievski, Ljupco Todorovski, Jus Kocijan, Saso Dzeroski:
Equation Discovery for Nonlinear System Identification. CoRR abs/1907.00821 (2019) - 2018
- [j82]Ivica Slavkov, Jana Karcheska, Dragi Kocev, Saso Dzeroski:
HMC-ReliefF: Feature ranking for hierarchical multi-label classification. Comput. Sci. Inf. Syst. 15(1): 187-209 (2018) - [j81]Ivica Slavkov, Matej Petkovic, Dragi Kocev, Saso Dzeroski:
Quantitative Score for Assessing the Quality of Feature Rankings. Informatica (Slovenia) 42(1) (2018) - [j80]Jurica Levatic, Dragi Kocev, Michelangelo Ceci, Saso Dzeroski:
Semi-supervised trees for multi-target regression. Inf. Sci. 450: 109-127 (2018) - [j79]Matej Mihelcic, Saso Dzeroski, Nada Lavrac, Tomislav Smuc:
Redescription mining augmented with random forest of multi-target predictive clustering trees. J. Intell. Inf. Syst. 50(1): 63-96 (2018) - [j78]Aljaz Osojnik, Pance Panov, Saso Dzeroski:
Tree-based methods for online multi-target regression. J. Intell. Inf. Syst. 50(2): 315-339 (2018) - [j77]Martin Breskvar, Dragi Kocev, Saso Dzeroski:
Ensembles for multi-target regression with random output selections. Mach. Learn. 107(11): 1673-1709 (2018) - [c147]Matej Petkovic, Dragi Kocev, Saso Dzeroski:
Feature Ranking with Relief for Multi-label Classification: Does Distance Matter? DS 2018: 51-65 - [c146]Matej Mihelcic, Saso Dzeroski, Tomislav Smuc:
Extending Redescription Mining to Multiple Views. DS 2018: 292-307 - [c145]Jihed Khiari, Luís Moreira-Matias, Ammar Shaker, Bernard Zenko, Saso Dzeroski:
MetaBags: Bagged Meta-Decision Trees for Regression. ECML/PKDD (1) 2018: 637-652 - [i6]Jihed Khiari, Luís Moreira-Matias, Ammar Shaker, Bernard Zenko, Saso Dzeroski:
MetaBags: Bagged Meta-Decision Trees for Regression. CoRR abs/1804.06207 (2018) - [i5]Matej Petkovic, Redouane Boumghar, Martin Breskvar, Saso Dzeroski, Dragi Kocev, Jurica Levatic, Luke Lucas, Aljaz Osojnik, Bernard Zenko, Nikola Simidjievski:
Machine learning for predicting thermal power consumption of the Mars Express Spacecraft. CoRR abs/1809.00542 (2018) - 2017
- [j76]Matej Mihelcic, Saso Dzeroski, Nada Lavrac, Tomislav Smuc:
A framework for redescription set construction. Expert Syst. Appl. 68: 196-215 (2017) - [j75]Gjorgji Madjarov, Dejan Gjorgjevikj, Ivica Dimitrovski, Saso Dzeroski:
Erratum to: The use of data-derived label hierarchies in multi-label classification. J. Intell. Inf. Syst. 48(2): 475-476 (2017) - [j74]Jurica Levatic, Michelangelo Ceci, Dragi Kocev, Saso Dzeroski:
Semi-supervised classification trees. J. Intell. Inf. Syst. 49(3): 461-486 (2017) - [j73]Jurica Levatic, Michelangelo Ceci, Dragi Kocev, Saso Dzeroski:
Self-training for multi-target regression with tree ensembles. Knowl. Based Syst. 123: 41-60 (2017) - [j72]Aljaz Osojnik, Pance Panov, Saso Dzeroski:
Multi-label classification via multi-target regression on data streams. Mach. Learn. 106(6): 745-770 (2017) - [c144]Mate Bestek, Dragi Kocev, Saso Dzeroski, Andrej Brodnik, Rade Iljaz:
Modelling Time-Series of Glucose Measurements from Diabetes Patients Using Predictive Clustering Trees. AIME 2017: 95-104 - [c143]Ziga Luksic, Jovan Tanevski, Saso Dzeroski, Ljupco Todorovski:
General Meta-Model Framework for Surrogate-Based Numerical Optimization. DS 2017: 51-66 - [c142]Martin Breskvar, Dragi Kocev, Saso Dzeroski:
Multi-label Classification Using Random Label Subset Selections. DS 2017: 108-115 - [c141]Tomaz Stepisnik Perdih, Aljaz Osojnik, Saso Dzeroski, Dragi Kocev:
Option Predictive Clustering Trees for Hierarchical Multi-label Classification. DS 2017: 116-123 - [c140]Matej Petkovic, Saso Dzeroski, Dragi Kocev:
Feature Ranking for Multi-target Regression with Tree Ensemble Methods. DS 2017: 171-185 - [c139]Valentin Gjorgjioski, Dragi Kocev, Andrej Boncina, Saso Dzeroski, Marko Debeljak:
Predictive Clustering of Multi-dimensional Time Series Applied to Forest Growing Stock Data for Different Tree Sizes. ICT Innovations 2017: 186-195 - [c138]Vanja Mileski, Saso Dzeroski, Dragi Kocev:
Predictive Clustering Trees for Hierarchical Multi-Target Regression. IDA 2017: 223-234 - [c137]Jurica Levatic, Maria Brbic, Tomaz Stepisnik Perdih, Dragi Kocev, Vedrana Vidulin, Tomislav Smuc, Fran Supek, Saso Dzeroski:
Phenotype Prediction with Semi-supervised Classification Trees. NFMCP@PKDD/ECML 2017: 138-150 - [c136]Stevanche Nikoloski, Dragi Kocev, Saso Dzeroski:
Structuring the Output Space in Multi-label Classification by Using Feature Ranking. NFMCP@PKDD/ECML 2017: 151-166 - [c135]Ivica Dimitrovski, Dragi Kocev, Suzana Loskovska, Saso Dzeroski:
Image Representation, Annotation and Retrieval with Predictive Clustering Trees. ECML/PKDD (3) 2017: 363-367 - [c134]Jovan Tanevski, Nikola Simidjievski, Ljupco Todorovski, Saso Dzeroski:
Process-Based Modeling and Design of Dynamical Systems. ECML/PKDD (3) 2017: 378-382 - [e13]Michelangelo Ceci, Jaakko Hollmén, Ljupco Todorovski, Celine Vens, Saso Dzeroski:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part I. Lecture Notes in Computer Science 10534, Springer 2017, ISBN 978-3-319-71248-2 [contents] - [e12]Michelangelo Ceci, Jaakko Hollmén, Ljupco Todorovski, Celine Vens, Saso Dzeroski:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part II. Lecture Notes in Computer Science 10535, Springer 2017, ISBN 978-3-319-71245-1 [contents] - [e11]Yasemin Altun, Kamalika Das, Taneli Mielikäinen, Donato Malerba, Jerzy Stefanowski, Jesse Read, Marinka Zitnik, Michelangelo Ceci, Saso Dzeroski:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part III. Lecture Notes in Computer Science 10536, Springer 2017, ISBN 978-3-319-71272-7 [contents] - [i4]Matej Mihelcic, Goran Simic, Mirjana Babic Leko, Nada Lavrac, Saso Dzeroski, Tomislav Smuc:
Using Redescription Mining to Relate Clinical and Biological Characteristics of Cognitively Impaired and Alzheimer's Disease Patients. CoRR abs/1702.06831 (2017) - [i3]Nikola Simidjievski, Jovan Tanevski, Bernard Zenko, Zoran Levnajic, Ljupco Todorovski, Saso Dzeroski:
Decoupling approximation robustly reconstructs directed dynamical networks. CoRR abs/1712.03100 (2017) - 2016
- [j71]Jovan Tanevski, Ljupco Todorovski, Saso Dzeroski:
Learning stochastic process-based models of dynamical systems from knowledge and data. BMC Syst. Biol. 10: 30 (2016) - [j70]Aljaz Osojnik, Pance Panov, Saso Dzeroski:
Modeling dynamical systems with data stream mining. Comput. Sci. Inf. Syst. 13(2): 453-473 (2016) - [j69]Ivica Dimitrovski, Dragi Kocev, Suzana Loskovska, Saso Dzeroski:
Improving bag-of-visual-words image retrieval with predictive clustering trees. Inf. Sci. 329: 851-865 (2016) - [j68]Pance Panov, Larisa N. Soldatova, Saso Dzeroski:
Generic ontology of datatypes. Inf. Sci. 329: 900-920 (2016) - [j67]Gjorgji Madjarov, Dejan Gjorgjevikj, Ivica Dimitrovski, Saso Dzeroski:
The use of data-derived label hierarchies in multi-label classification. J. Intell. Inf. Syst. 47(1): 57-90 (2016) - [j66]Saso Dzeroski, Dragi Kocev, Pance Panov:
Special issue on discovery science. Mach. Learn. 105(1): 1-2 (2016) - [j65]Darko Aleksovski, Jus Kocijan, Saso Dzeroski:
Ensembles of Fuzzy Linear Model Trees for the Identification of Multioutput Systems. IEEE Trans. Fuzzy Syst. 24(4): 916-929 (2016) - [c133]Aljaz Osojnik, Saso Dzeroski, Dragi Kocev:
Option Predictive Clustering Trees for Multi-target Regression. DS 2016: 118-133 - [c132]Nikola Simidjievski, Ljupco Todorovski, Saso Dzeroski:
Learning Ensembles of Process-Based Models by Bagging of Random Library Samples. DS 2016: 245-260 - [c131]Matej Petkovic, Pance Panov, Saso Dzeroski:
A Comparison of Different Data Transformation Approaches in the Feature Ranking Context. DS 2016: 310-324 - [c130]Saso Dzeroski:
Learning from Massive, Incompletely annotated & Structured Data. EGC 2016: 7-8 - [c129]Michelangelo Ceci, Gianvito Pio, Vladimir Kuzmanovski, Saso Dzeroski:
Semi-Supervised Multi-View Learning for Gene Network Reconstruction. SEBD 2016: 198-205 - [c128]Agnieszka Lawrynowicz, Diego Esteves, Pance Panov, Tommaso Soru, Saso Dzeroski, Joaquin Vanschoren:
An Algorithm, Implementation and Execution Ontology Design Pattern. WOP@ISWC 2016: 55-68 - [i2]Matej Mihelcic, Saso Dzeroski, Nada Lavrac, Tomislav Smuc:
A framework for redescription set construction. CoRR abs/1606.03935 (2016) - 2015
- [j64]Darko Aleksovski, Jus Kocijan, Saso Dzeroski:
Model-Tree Ensembles for noise-tolerant system identification. Adv. Eng. Informatics 29(1): 1-15 (2015) - [j63]Jovan Tanevski, Ljupco Todorovski, Yannis Kalaidzidis, Saso Dzeroski:
Domain-specific model selection for structural identification of the Rab5-Rab7 dynamics in endocytosis. BMC Syst. Biol. 9: 31 (2015) - [j62]Ivica Dimitrovski, Dragi Kocev, Ivan Kitanovski, Suzana Loskovska, Saso Dzeroski:
Improved medical image modality classification using a combination of visual and textual features. Comput. Medical Imaging Graph. 39: 14-26 (2015) - [j61]Nikola Simidjievski, Ljupco Todorovski, Saso Dzeroski:
Predicting long-term population dynamics with bagging and boosting of process-based models. Expert Syst. Appl. 42(22): 8484-8496 (2015) - [j60]Elena Ikonomovska, João Gama, Saso Dzeroski:
Online tree-based ensembles and option trees for regression on evolving data streams. Neurocomputing 150: 458-470 (2015) - [j59]Jurica Levatic, Dragi Kocev, Saso Dzeroski:
The importance of the label hierarchy in hierarchical multi-label classification. J. Intell. Inf. Syst. 45(2): 247-271 (2015) - [c127]Aljaz Osojnik, Pance Panov, Saso Dzeroski:
Multi-label Classification via Multi-target Regression on Data Streams. Discovery Science 2015: 170-185 - [c126]Pance Panov, Larisa N. Soldatova, Saso Dzeroski:
Representing bioinformatics datatypes using the OntoDT ontology. ICBO 2015 - [c125]Larisa N. Soldatova, Pance Panov, Saso Dzeroski:
Ontology Engineering: From an Art to a Craft - The Case of the Data Mining Ontologies. OWLED 2015: 174-181 - [c124]Aljaz Osojnik, Pance Panov, Saso Dzeroski:
Comparison of Tree-Based Methods for Multi-target Regression on Data Streams. NFMCP 2015: 17-31 - [c123]Matej Mihelcic, Saso Dzeroski, Nada Lavrac, Tomislav Smuc:
Redescription Mining with Multi-target Predictive Clustering Trees. NFMCP 2015: 125-143 - [c122]Jurica Levatic, Michelangelo Ceci, Dragi Kocev, Saso Dzeroski:
Semi-supervised learning for multi-target regression (Discussion paper). SEBD 2015: 240-247 - 2014
- [j58]Pance Panov, Larisa N. Soldatova, Saso Dzeroski:
Ontology of core data mining entities. Data Min. Knowl. Discov. 28(5-6): 1222-1265 (2014) - [j57]Mateja Skerjanec, Natasa Atanasova, Darko Cerepnalkoski, Saso Dzeroski, Boris Kompare:
Development of a knowledge library for automated watershed modeling. Environ. Model. Softw. 54: 60-72 (2014) - [j56]Ivica Dimitrovski, Dragi Kocev, Suzana Loskovska, Saso Dzeroski:
Fast and efficient visual codebook construction for multi-label annotation using predictive clustering trees. Pattern Recognit. Lett. 38: 38-45 (2014) - [c121]Rok Piltaver, Mitja Lustrek, Jernej Zupancic, Saso Dzeroski, Matjaz Gams:
Multi-objective learning of hybrid classifiers. ECAI 2014: 717-722 - [c120]Darko Aleksovski, Jus Kocijan, Saso Dzeroski:
Model Tree Ensembles for the Identification of Multiple-Output Systems. ECC 2014: 750-755 - [c119]Jurica Levatic, Michelangelo Ceci, Dragi Kocev, Saso Dzeroski:
Semi-supervised Learning for Multi-target Regression. NFMCP 2014: 3-18 - [c118]Gjorgji Madjarov, Ivica Dimitrovski, Dejan Gjorgjevikj, Saso Dzeroski:
Evaluation of Different Data-Derived Label Hierarchies in Multi-label Classification. NFMCP 2014: 19-37 - [e10]Saso Dzeroski, Pance Panov, Dragi Kocev, Ljupco Todorovski:
Discovery Science - 17th International Conference, DS 2014, Bled, Slovenia, October 8-10, 2014. Proceedings. Lecture Notes in Computer Science 8777, Springer 2014, ISBN 978-3-319-11811-6 [contents] - 2013
- [j55]Daniela Stojanova, Michelangelo Ceci, Annalisa Appice, Donato Malerba, Saso Dzeroski:
Dealing with spatial autocorrelation when learning predictive clustering trees. Ecol. Informatics 13: 22-39 (2013) - [j54]Dragi Kocev, Saso Dzeroski:
Habitat modeling with single- and multi-target trees and ensembles. Ecol. Informatics 18: 79-92 (2013) - [j53]Dejan Gjorgjevikj, Gjorgji Madjarov, Saso Dzeroski:
Hybrid Decision Tree Architecture Utilizing Local SVMs for Efficient Multi-Label Learning. Int. J. Pattern Recognit. Artif. Intell. 27(7) (2013) - [j52]Jurica Levatic, Saso Dzeroski, Fran Supek, Tomislav Smuc:
Semi-Supervised Learning for Quantitative Structure-Activity Modeling. Informatica (Slovenia) 37(2): 173-179 (2013) - [j51]Nives Skunca, Matko Bosnjak, Anita Krisko, Pance Panov, Saso Dzeroski, Tomislav Smuc, Fran Supek:
Phyletic Profiling with Cliques of Orthologs Is Enhanced by Signatures of Paralogy Relationships. PLoS Comput. Biol. 9(1) (2013) - [j50]Dragi Kocev, Celine Vens, Jan Struyf, Saso Dzeroski:
Tree ensembles for predicting structured outputs. Pattern Recognit. 46(3): 817-833 (2013) - [c117]Darko Aleksovski, Jus Kocijan, Saso Dzeroski:
Model Tree Ensembles for Modeling Dynamic Systems. Discovery Science 2013: 17-32 - [c116]Ivica Dimitrovski, Dragi Kocev, Suzana Loskovska, Saso Dzeroski:
Fast and Scalable Image Retrieval Using Predictive Clustering Trees. Discovery Science 2013: 33-48 - [c115]Pance Panov, Larisa N. Soldatova, Saso Dzeroski:
OntoDM-KDD: Ontology for Representing the Knowledge Discovery Process. Discovery Science 2013: 126-140 - [c114]Daniela Stojanova, Michelangelo Ceci, Donato Malerba, Saso Dzeroski:
Learning Hierarchical Multi-label Classification Trees from Network Data. Discovery Science 2013: 233-248 - [c113]Jovan Tanevski, Ljupco Todorovski, Yannis Kalaidzidis, Saso Dzeroski:
Inductive Process Modeling of Rab5-Rab7 Conversion in Endocytosis. Discovery Science 2013: 265-280 - [c112]Ivica Slavkov, Jana Karcheska, Dragi Kocev, Slobodan Kalajdziski, Saso Dzeroski:
ReliefF for Hierarchical Multi-label Classification. NFMCP 2013: 148-161 - [c111]Jurica Levatic, Dragi Kocev, Saso Dzeroski:
The Use of the Label Hierarchy in Hierarchical Multi-label Classification Improves Performance. NFMCP 2013: 162-177 - 2012
- [j49]Daniela Stojanova, Andrej Kobler, Peter Ogrinc, Bernard Zenko, Saso Dzeroski:
Estimating the risk of fire outbreaks in the natural environment. Data Min. Knowl. Discov. 24(2): 411-442 (2012) - [j48]Daniela Stojanova, Michelangelo Ceci, Annalisa Appice, Saso Dzeroski:
Network regression with predictive clustering trees. Data Min. Knowl. Discov. 25(2): 378-413 (2012) - [j47]Ivica Dimitrovski, Dragi Kocev, Suzana Loskovska, Saso Dzeroski:
Hierarchical classification of diatom images using ensembles of predictive clustering trees. Ecol. Informatics 7(1): 19-29 (2012) - [j46]Timo Aho, Bernard Zenko, Saso Dzeroski, Tapio Elomaa:
Multi-target regression with rule ensembles. J. Mach. Learn. Res. 13: 2367-2407 (2012) - [j45]Gjorgji Madjarov, Dejan Gjorgjevikj, Saso Dzeroski:
Two stage architecture for multi-label learning. Pattern Recognit. 45(3): 1019-1034 (2012) - [j44]Gjorgji Madjarov, Dragi Kocev, Dejan Gjorgjevikj, Saso Dzeroski:
An extensive experimental comparison of methods for multi-label learning. Pattern Recognit. 45(9): 3084-3104 (2012) - 2011
- [j43]Katerina Tashkova, Peter Korosec, Jurij Silc, Ljupco Todorovski, Saso Dzeroski:
Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis. BMC Syst. Biol. 5: 159 (2011) - [j42]