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Dragi Kocev
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2020 – today
- 2024
- [j46]Jurica Levatic
, Michelangelo Ceci
Semi-Supervised Predictive Clustering Trees for (Hierarchical) Multi-Label Classification. Int. J. Intell. Syst. 2024: 1-21 (2024) - [j45]Ivica Dimitrovski
In-Domain Self-Supervised Learning Improves Remote Sensing Image Scene Classification. IEEE Geosci. Remote. Sens. Lett. 21: 1-5 (2024) - [j44]Marjan Stoimchev
Semi-Supervised Multi-Label Classification of Land Use/Land Cover in Remote Sensing Images With Predictive Clustering Trees and Ensembles. IEEE Trans. Geosci. Remote. Sens. 62: 1-16 (2024) - 2023
- [j43]Matej Petkovic, Saso Dzeroski, Dragi Kocev
Feature ranking for semi-supervised learning. Mach. Learn. 112(11): 4379-4408 (2023) - [j42]Marjan Stoimchev
Deep Network Architectures as Feature Extractors for Multi-Label Classification of Remote Sensing Images. Remote. Sens. 15(2): 538 (2023) - [j41]Ivica Dimitrovski
AiTLAS: Artificial Intelligence Toolbox for Earth Observation. Remote. Sens. 15(9): 2343 (2023) - [j40]Matej Petkovic, Jurica Levatic, Dragi Kocev, Martin Breskvar, Saso Dzeroski:
CLUSplus: A decision tree-based framework for predicting structured outputs. SoftwareX 24: 101526 (2023) - [i16]Ivica Dimitrovski, Ivan Kitanovski, Nikola Simidjievski, Dragi Kocev:
In-Domain Self-Supervised Learning Can Lead to Improvements in Remote Sensing Image Classification. CoRR abs/2307.01645 (2023) - 2022
- [j39]Jasmin Bogatinovski
Comprehensive comparative study of multi-label classification methods. Expert Syst. Appl. 203: 117215 (2022) - [j38]Jasmin Bogatinovski, Ljupco Todorovski, Saso Dzeroski
Explaining the performance of multilabel classification methods with data set properties. Int. J. Intell. Syst. 37(9): 6080-6122 (2022) - [c37]Elena Merdjanovska, Ivan Kitanovski, Ziga Kokalj, Ivica Dimitrovski
Crop Type Prediction Across Countries and Years: Slovenia, Denmark and the Netherlands. IGARSS 2022: 5945-5948 - [c36]Ana Kostovska
Explainable Model-specific Algorithm Selection for Multi-Label Classification. SSCI 2022: 39-46 - [i15]Ivica Dimitrovski, Ivan Kitanovski, Pance Panov, Nikola Simidjievski, Dragi Kocev:
AiTLAS: Artificial Intelligence Toolbox for Earth Observation. CoRR abs/2201.08789 (2022) - [i14]Ivica Dimitrovski
Current Trends in Deep Learning for Earth Observation: An Open-source Benchmark Arena for Image Classification. CoRR abs/2207.07189 (2022) - [i13]Jurica Levatic, Michelangelo Ceci, Dragi Kocev
Semi-supervised Predictive Clustering Trees for (Hierarchical) Multi-label Classification. CoRR abs/2207.09237 (2022) - [i12]Dragi Kocev
Discover the Mysteries of the Maya: Selected Contributions from the Machine Learning Challenge & The Discovery Challenge Workshop at ECML PKDD 2021. CoRR abs/2208.03163 (2022) - [i11]Ana Kostovska, Carola Doerr, Saso Dzeroski, Dragi Kocev
Explainable Model-specific Algorithm Selection for Multi-Label Classification. CoRR abs/2211.11227 (2022) - [i10]Ana Kostovska, Jasmin Bogatinovski, Andrej Treven, Saso Dzeroski, Dragi Kocev
FAIRification of MLC data. CoRR abs/2211.12757 (2022) - 2021
- [j37]Matej Petkovic
Fuzzy Jaccard Index: A robust comparison of ordered lists. Appl. Soft Comput. 113(Part): 107849 (2021) - [j36]Tome Eftimov, Bibek Paudel, Gorjan Popovski
A Framework for Evaluating Personalized Ranking Systems by Fusing Different Evaluation Measures. Big Data Res. 25: 100211 (2021) - [j35]Matej Petkovic
Biomarker discovery by feature ranking: Evaluation on a case study of embryonal tumors. Comput. Biol. Medicine 128: 104143 (2021) - [j34]Tomaz Stepisnik, Blaz Skrlj, Jörg Wicker
A comprehensive comparison of molecular feature representations for use in predictive modeling. Comput. Biol. Medicine 130: 104197 (2021) - [j33]Stevanche Nikoloski
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) - [j32]Matej Petkovic
Ensemble- and distance-based feature ranking for unsupervised learning. Int. J. Intell. Syst. 36(7): 3068-3086 (2021) - [j31]Tomaz Stepisnik, Dragi Kocev
Oblique predictive clustering trees. Knowl. Based Syst. 227: 107228 (2021) - [j30]Tomaz Stepisnik, Dragi Kocev
Semi-supervised oblique predictive clustering trees. PeerJ Comput. Sci. 7: e506 (2021) - [i9]Jasmin Bogatinovski, Ljupco Todorovski, Saso Dzeroski, Dragi Kocev:
Comprehensive Comparative Study of Multi-Label Classification Methods. CoRR abs/2102.07113 (2021) - [i8]Jasmin Bogatinovski, Ljupco Todorovski, Saso Dzeroski, Dragi Kocev:
Explaining the Performance of Multi-label Classification Methods with Data Set Properties. CoRR abs/2106.15411 (2021) - [i7]Ana Kostovska, Matej Petkovic, Tomaz Stepisnik, Luke Lucas, Timothy Finn, José Antonio Martínez Heras, Pance Panov, Saso Dzeroski, Alessandro Donati, Nikola Simidjievski, Dragi Kocev:
GalaxAI: Machine learning toolbox for interpretable analysis of spacecraft telemetry data. CoRR abs/2108.01407 (2021) - [i6]Matej Petkovic, Luke Lucas, Tomaz Stepisnik, Pance Panov, Nikola Simidjievski, Dragi Kocev:
Discovering outliers in the Mars Express thermal power consumption patterns. CoRR abs/2108.02067 (2021) - 2020
- [j29]Tomaz Stepisnik, Aljaz Osojnik
Option predictive clustering trees for multi-target regression. Comput. Sci. Inf. Syst. 17(2): 459-486 (2020) - [j28]Jurica Levatic, Michelangelo Ceci
Semi-supervised regression trees with application to QSAR modelling. Expert Syst. Appl. 158: 113569 (2020) - [j27]Matej Petkovic
Feature ranking for multi-target regression. Mach. Learn. 109(6): 1179-1204 (2020) - [j26]Matej Petkovic
Multi-label feature ranking with ensemble methods. Mach. Learn. 109(11): 2141-2159 (2020) - [j25]Dragi Kocev
Ensembles of extremely randomized predictive clustering trees for predicting structured outputs. Mach. Learn. 109(11): 2213-2241 (2020) - [j24]Ivica Slavkov, Matej Petkovic
Error curves for evaluating the quality of feature rankings. PeerJ Comput. Sci. 6: e310 (2020) - [c35]Tome Eftimov, Gorjan Popovski, Dragi Kocev
Performance2vec: a step further in explainable stochastic optimization algorithm performance. GECCO Companion 2020: 193-194 - [c34]Tomaz Stepisnik, Dragi Kocev
Hyperbolic Embeddings for Hierarchical Multi-label Classification. ISMIS 2020: 66-76 - [c33]Tomaz Stepisnik
Multivariate Predictive Clustering Trees for Classification. ISMIS 2020: 331-341 - [i5]Tomaz Stepisnik, Dragi Kocev:
Oblique Predictive Clustering Trees. CoRR abs/2007.13617 (2020) - [i4]Matej Petkovic, Blaz Skrlj, Dragi Kocev, Nikola Simidjievski:
Fuzzy Jaccard Index: A robust comparison of ordered lists. CoRR abs/2008.02216 (2020) - [i3]Matej Petkovic, Saso Dzeroski, Dragi Kocev:
Feature Ranking for Semi-supervised Learning. CoRR abs/2008.03937 (2020) - [i2]Matej Petkovic, Dragi Kocev, Blaz Skrlj, Saso Dzeroski:
Ensemble- and Distance-Based Feature Ranking for Unsupervised Learning. CoRR abs/2011.11679 (2020)
2010 – 2019
- 2019
- [j23]Stevanche Nikoloski
Data-Driven Structuring of the Output Space Improves the Performance of Multi-Target Regressors. IEEE Access 7: 145177-145198 (2019) - [j22]Gjorgji Madjarov, Vedrana Vidulin, Ivica Dimitrovski
Web genre classification with methods for structured output prediction. Inf. Sci. 503: 551-573 (2019) - [c32]Tome Eftimov, Dragi Kocev:
Performance Measures Fusion for Experimental Comparison of Methods for Multi-label Classification. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering 2019 - [c31]Bibek Paudel, Dragi Kocev
Mix and Rank: A Framework for Benchmarking Recommender Systems. IEEE BigData 2019: 3717-3726 - [c30]Bozhidar Stevanoski, Dragi Kocev
Predicting Thermal Power Consumption of the Mars Express Satellite with Data Stream Mining. DS 2019: 186-201 - [c29]Matej Petkovic
Ensemble-Based Feature Ranking for Semi-supervised Classification. DS 2019: 290-305 - [c28]Jasmin Bogatinovski, Dragi Kocev
Feature Extraction for Heartbeat Classification in Single-Lead ECG. MIPRO 2019: 320-325 - 2018
- [j21]Ivica Slavkov, Jana Karcheska, Dragi Kocev
HMC-ReliefF: Feature ranking for hierarchical multi-label classification. Comput. Sci. Inf. Syst. 15(1): 187-209 (2018) - [j20]Ivica Slavkov, Matej Petkovic, Dragi Kocev, Saso Dzeroski:
Quantitative Score for Assessing the Quality of Feature Rankings. Informatica (Slovenia) 42(1) (2018) - [j19]Jurica Levatic
Semi-supervised trees for multi-target regression. Inf. Sci. 450: 109-127 (2018) - [j18]Martin Breskvar
Ensembles for multi-target regression with random output selections. Mach. Learn. 107(11): 1673-1709 (2018) - [c27]Matej Petkovic
Feature Ranking with Relief for Multi-label Classification: Does Distance Matter? DS 2018: 51-65 - [i1]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
- [j17]Kurt Driessens
Introduction to the special issue dedicated to the Journal Track of ECML PKDD 2017. Data Min. Knowl. Discov. 31(5): 1155-1156 (2017) - [j16]Jurica Levatic
Semi-supervised classification trees. J. Intell. Inf. Syst. 49(3): 461-486 (2017) - [j15]Jurica Levatic
Self-training for multi-target regression with tree ensembles. Knowl. Based Syst. 123: 41-60 (2017) - [j14]Kurt Driessens
Introduction to the special issue dedicated to the Journal Track of ECML PKDD 2017. Mach. Learn. 106(9-10): 1243-1244 (2017) - [c26]Mate Bestek, Dragi Kocev
Modelling Time-Series of Glucose Measurements from Diabetes Patients Using Predictive Clustering Trees. AIME 2017: 95-104 - [c25]Martin Breskvar
Multi-label Classification Using Random Label Subset Selections. DS 2017: 108-115 - [c24]Tomaz Stepisnik Perdih, Aljaz Osojnik
Option Predictive Clustering Trees for Hierarchical Multi-label Classification. DS 2017: 116-123 - [c23]Matej Petkovic
Feature Ranking for Multi-target Regression with Tree Ensemble Methods. DS 2017: 171-185 - [c22]Valentin Gjorgjioski, Dragi Kocev
Predictive Clustering of Multi-dimensional Time Series Applied to Forest Growing Stock Data for Different Tree Sizes. ICT Innovations 2017: 186-195 - [c21]Vanja Mileski, Saso Dzeroski
Predictive Clustering Trees for Hierarchical Multi-Target Regression. IDA 2017: 223-234 - [c20]Jurica Levatic, Maria Brbic
Phenotype Prediction with Semi-supervised Classification Trees. NFMCP@PKDD/ECML 2017: 138-150 - [c19]Stevanche Nikoloski
Structuring the Output Space in Multi-label Classification by Using Feature Ranking. NFMCP@PKDD/ECML 2017: 151-166 - [c18]Ivica Dimitrovski
Image Representation, Annotation and Retrieval with Predictive Clustering Trees. ECML/PKDD (3) 2017: 363-367 - 2016
- [j13]Ivica Dimitrovski
Improving bag-of-visual-words image retrieval with predictive clustering trees. Inf. Sci. 329: 851-865 (2016) - [j12]Saso Dzeroski
Special issue on discovery science. Mach. Learn. 105(1): 1-2 (2016) - [c17]Aljaz Osojnik
Option Predictive Clustering Trees for Multi-target Regression. DS 2016: 118-133 - [c16]Aleksandra Rashkovska
Clustering of heartbeats from ECG recordings obtained with wireless body sensors. MIPRO 2016: 461-466 - 2015
- [j11]Ivica Dimitrovski
Improved medical image modality classification using a combination of visual and textual features. Comput. Medical Imaging Graph. 39: 14-26 (2015) - [j10]Aleksandra Rashkovska
Non-invasive real-time prediction of inner knee temperatures during therapeutic cooling. Comput. Methods Programs Biomed. 122(2): 136-148 (2015) - [j9]Jurica Levatic
The importance of the label hierarchy in hierarchical multi-label classification. J. Intell. Inf. Syst. 45(2): 247-271 (2015) - [c15]Dragi Kocev
Ensembles of Extremely Randomized Trees for Multi-target Regression. Discovery Science 2015: 86-100 - [c14]Gjorgji Madjarov
Web Genre Classification via Hierarchical Multi-label Classification. IDEAL 2015: 9-17 - [c13]Jurica Levatic, Michelangelo Ceci, Dragi Kocev, Saso Dzeroski:
Semi-supervised learning for multi-target regression (Discussion paper). SEBD 2015: 240-247 - 2014
- [j8]Ivica Dimitrovski
Fast and efficient visual codebook construction for multi-label annotation using predictive clustering trees. Pattern Recognit. Lett. 38: 38-45 (2014) - [c12]Ivica Dimitrovski, Gjorgji Madjarov, Dragi Kocev, Petre Lameski:
Maestra at LifeCLEF 2014 Plant Task: Plant Identification using Visual Data. CLEF (Working Notes) 2014: 705-714 - [c11]Jurica Levatic
Semi-supervised Learning for Multi-target Regression. NFMCP 2014: 3-18 - [e1]Saso Dzeroski
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
- [j7]Dragi Kocev
Habitat modeling with single- and multi-target trees and ensembles. Ecol. Informatics 18: 79-92 (2013) - [j6]Dragi Kocev
Tree ensembles for predicting structured outputs. Pattern Recognit. 46(3): 817-833 (2013) - [c10]Ivica Dimitrovski
Fast and Scalable Image Retrieval Using Predictive Clustering Trees. Discovery Science 2013: 33-48 - [c9]Ivica Slavkov, Jana Karcheska, Dragi Kocev
ReliefF for Hierarchical Multi-label Classification. NFMCP 2013: 148-161 - [c8]Jurica Levatic
The Use of the Label Hierarchy in Hierarchical Multi-label Classification Improves Performance. NFMCP 2013: 162-177 - 2012
- [j5]Ivica Dimitrovski
Hierarchical classification of diatom images using ensembles of predictive clustering trees. Ecol. Informatics 7(1): 19-29 (2012) - [j4]Dragi Kocev:
Ensembles for Predicting Structured Outputs. Informatica (Slovenia) 36(1): 113-114 (2012) - [j3]Gjorgji Madjarov
An extensive experimental comparison of methods for multi-label learning. Pattern Recognit. 45(9): 3084-3104 (2012) - 2011
- [j2]Ivica Dimitrovski
Hierarchical annotation of medical images. Pattern Recognit. 44(10-11): 2436-2449 (2011) - 2010
- [j1]Leander Schietgat, Celine Vens, Jan Struyf, Hendrik Blockeel
Predicting gene function using hierarchical multi-label decision tree ensembles. BMC Bioinform. 11: 2 (2010) - [c7]Ivica Dimitrovski, Dragi Kocev, Suzana Loskovska, Saso Dzeroski:
Detection of Visual Concepts and Annotation of Images Using Predictive Clustering Trees. CLEF (Notebook Papers/LABs/Workshops) 2010 - [c6]Ivica Dimitrovski
Detection of Visual Concepts and Annotation of Images Using Ensembles of Trees for Hierarchical Multi-Label Classification. ICPR Contests 2010: 152-161 - [p1]Celine Vens, Leander Schietgat, Jan Struyf, Hendrik Blockeel
Predicting Gene Function using Predictive Clustering Trees. Inductive Databases and Constraint-Based Data Mining 2010: 365-387
2000 – 2009
- 2009
- [c5]Ivica Dimitrovski
ImageCLEF 2009 Medical Image Annotation Task: PCTs for Hierarchical Multi-Label Classification. CLEF (2) 2009: 231-238 - [c4]Ivica Dimitrovski, Dragi Kocev, Suzana Loskovska, Saso Dzeroski:
ImageCLEF 2009 Medical Image Annotation Task: PCTs for Hierarchical Multi-Label Classification. CLEF (Working Notes) 2009 - [c3]Andreja Naumoski, Dragi Kocev
Predicting chemical parameters of the water from diatom abudance in lake Prespa and its tributaries. ITEE 2009: 264-277 - 2007
- [c2]Dragi Kocev
Ensembles of Multi-Objective Decision Trees. ECML 2007: 624-631 - 2006
- [c1]Dragi Kocev
Beam Search Induction and Similarity Constraints for Predictive Clustering Trees. KDID 2006: 134-151
Coauthor Index
[j46] [j44] [j43] [j42] [j40] [j39] [j38] [c36] [i13] [i11] [i10] [j35] [j33] [j32] [i9] [i8] [i7] [j29] [j28] [j27] [j26] [j24] [i3] [i2] [j23] [c30] [c29] [j21] [j20] [j19] [j18] [c27] [i1] [j16] [j15] [c26] [c25] [c24] [c23] [c22] [c21] [c20] [c19] [c18] [j13] [j12] [c17] [j11] [j9] [c13] [j8] [c11] [e1] [j7] [j6] [c10] [c9] [c8] [j5] [j3] [j2] [j1] [c7] [c6] [p1] [c5] [c4] [c3] [c2] [c1]
Tomaz Stepisnik Perdih
aka: Tomaz Stepisnik
aka: Tomaz Stepisnik
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last updated on 2024-08-23 18:34 CEST by the dblp team
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