D. Kocev

发表

Using single- and multi-target regression trees and ensembles to model a compound index of vegetation condition

S. Džeroski, D. Kocev, M. White, 2009 .

An extensive experimental comparison of methods for multi-label learning

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

Semi-supervised Learning for Multi-target Regression

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

Probabilistic Active Learning : Towards Combining Versatility , Optimality and Efficiency

D. Kocev, P. Panov, S. Deroski, 2014 .

Hyperbolic Embeddings for Hierarchical Multi-label Classification

Dragi Kocev, Tomaz Stepisnik, D. Kocev, 2020, ISMIS.

Community structure models are improved by exploiting taxonomic rank with predictive clustering trees

S. Džeroski, D. Kocev, M. Debeljak, 2015 .

Learning habitat models for the diatom community in Lake Prespa

Sašo Džeroski, Dragi Kocev, Andreja Naumoski, 2010 .

Hierarchical Classification of Diatom Images using Predictive Clustering Trees

S. Džeroski, D. Kocev, I. Dimitrovski, 2010 .

Decomposition of the output space in multi-label classification using feature ranking

S. Džeroski, D. Kocev, Stevanche Nikoloski, 2017 .

ENSEMBLES OF MULTI-OBJECTIVE REGRESSION TREES: A CASE STUDY FOR PREDICTING THE CONDITION OF REMNANT INDIGENOUS VEGETATION

S. Džeroski, D. Kocev, M. White, 2007 .

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

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

A catalogue with semantic annotations makes multilabel datasets FAIR

S. Džeroski, D. Kocev, P. Panov, 2022, Scientific reports.

COMPARISON OF DISTANCES FOR MULTI-LABEL CLASSIFICATION WITH PCTs

S. Džeroski, D. Kocev, Valentin Gjorgjioski, 2011 .

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

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

Machine-learning ready data on the thermal power consumption of the Mars Express Spacecraft

S. Džeroski, D. Kocev, P. Panov, 2022, Scientific data.

Error curves for evaluating the quality of feature rankings

Pierre Geurts, Dragi Kocev, Sašo Džeroski, 2020, PeerJ Comput. Sci..

Current Trends in Deep Learning for Earth Observation: An Open-source Benchmark Arena for Image Classification

D. Kocev, I. Dimitrovski, N. Simidjievski, 2022, 2207.07189.

Discover the Mysteries of the Maya: Selected Contributions from the Machine Learning Challenge & The Discovery Challenge Workshop at ECML PKDD 2021

D. Kocev, Žiga Kokalj, I. Dimitrovski, 2022, ArXiv.

Semi-supervised Predictive Clustering Trees for (Hierarchical) Multi-label Classification

S. Džeroski, D. Kocev, Michelangelo Ceci, 2022, International Journal of Intelligent Systems.

Machine learning for effective spacecraft operation: Operating INTEGRAL through dynamic radiation environments

S. Džeroski, D. Kocev, P. Panov, 2022, Advances in Space Research.

Ensembles of extremely randomized predictive clustering trees for predicting structured outputs

D. Kocev, Michelangelo Ceci, Tomaz Stepisnik, 2020, Machine Learning.

Ensembles for multi-target regression with random output selections

S. Džeroski, D. Kocev, M. Breskvar, 2018, Machine Learning.

FAIRification of MLC data

S. Džeroski, D. Kocev, P. Panov, 2022, ArXiv.

Explainable Model-specific Algorithm Selection for Multi-Label Classification

S. Džeroski, D. Kocev, P. Panov, 2022, 2022 IEEE Symposium Series on Computational Intelligence (SSCI).

Inferential Modelling of Population Dynamics

S. Džeroski, D. Kocev, H. Cao, 2018 .

Current Trends in Deep Learning for Earth Observation: An Open-source Benchmark Arena for Image Classification

D. Kocev, I. Dimitrovski, N. Simidjievski, 2022, ISPRS Journal of Photogrammetry and Remote Sensing.

Discovery Science

Sašo Džeroski, Ljupco Todorovski, Dragi Kocev, 2014, Lecture Notes in Computer Science.

Oblique Predictive Clustering Trees pdf

Dragi Kocev, Tomaz Stepisnik, D. Kocev, 2020, Knowl. Based Syst..

Exploiting partially-labeled data in learning predictive clustering trees for multi-target regression: A case study of water quality assessment in Ireland

Sašo Džeroski, Dragi Kocev, Stevanche Nikoloski, 2020, Ecol. Informatics.

Semi-supervised trees for multi-target regression

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

ZEOLITES AS ALCOHOL ADSORBENTS FROM AQUEOUS SOLUTIONS

D. Kocev, Blagica Cekova, D. Stojanova, 2006 .

Multi-label feature ranking with ensemble methods

Sašo Džeroski, Dragi Kocev, Matej Petković, 2020, Machine Learning.

Data-Driven Structuring of the Output Space Improves the Performance of Multi-Target Regressors

Dragi Kocev, Sašo Džeroski, Stevanche Nikoloski, 2019, IEEE Access.

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.

Combined chemical genetics and data-driven bioinformatics approach identifies receptor tyrosine kinase inhibitors as host-directed antimicrobials

S. Džeroski, D. Kocev, T. Ottenhoff, 2018, Nature Communications.

Trait‐based risk assessment for invasive species: high performance across diverse taxonomic groups, geographic ranges and machine learning/statistical tools

Dragi Kocev, Sašo Džeroski, Reuben P. Keller, 2011 .

Biomarker discovery by feature ranking: Evaluation on a case study of embryonal tumors

Dragi Kocev, Sašo Džeroski, Ivica Slavkov, 2020, Comput. Biol. Medicine.

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

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

Wet-dry-wet drug screen leads to the synthesis of TS1, a novel compound reversing lung fibrosis through inhibition of myofibroblast differentiation

S. Džeroski, D. Kocev, P. Panov, 2021, Cell Death & Disease.

Tree ensembles for predicting structured outputs

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

Predicting Gene Function using Predictive Clustering Trees

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

Semi-supervised classification trees

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

Self-training for multi-target regression with tree ensembles

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

Predicting gene function using hierarchical multi-label decision tree ensembles

Saso Dzeroski, Celine Vens, Hendrik Blockeel, 2010, BMC Bioinformatics.

Predicting gene function in S. cerevisiae and A. thaliana using hierarchical multi-label decision tree ensembles

Celine Vens, Hendrik Blockeel, Jan Struyf, 2008 .

Fast and efficient visual codebook construction for multi-label annotation using predictive clustering trees

Saso Dzeroski, Ivica Dimitrovski, Suzana Loskovska, 2014, Pattern Recognit. Lett..

Semi-supervised oblique predictive clustering trees

Dragi Kocev, Tomaz Stepisnik, D. Kocev, 2021, PeerJ Comput. Sci..

Fuzzy Jaccard Index: A robust comparison of ordered lists pdf

Nikola Simidjievski, Blaz Skrlj, Dragi Kocev, 2020, Appl. Soft Comput..

Feature ranking for multi-target regression

Dragi Kocev, Sašo Džeroski, Matej Petković, 2019, Machine Learning.

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

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

Using machine learning to estimate herbage production and nutrient uptake on Irish dairy farms.

S. Džeroski, D. Kocev, D. Wall, 2019, Journal of dairy science.

COVID-19 pandemic changes the food consumption patterns

Tome Eftimov, Barbara Koroušić Seljak, Dragi Kocev, 2020, Trends in Food Science & Technology.

Special issue on discovery science

Saso Dzeroski, Dragi Kocev, Pance Panov, 2016, Machine Learning.

A comprehensive comparison of molecular feature representations for use in predictive modeling

Dragi Kocev, Jörg Wicker, Blaž Škrlj, 2021, Comput. Biol. Medicine.

Chaophilic or chaotolerant fungi: a new category of extremophiles?

S. Džeroski, D. Kocev, N. Gunde-Cimerman, 2014, Front. Microbiol..

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

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

Ensembles of extremely randomized predictive clustering trees for predicting structured outputs

Michelangelo Ceci, Dragi Kocev, Tomaž Stepišnik, 2020, Machine Learning.

Ensembles of Extremely Randomized Trees for Multi-target Regression

Michelangelo Ceci, Dragi Kocev, D. Kocev, 2015, Discovery Science.

Comprehensive Comparative Study of Multi-Label Classification Methods pdf

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

Hierarchical annotation of medical images

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

Using data mining to predict soil quality after application of biosolids in agriculture.

Sašo Džeroski, Marko Debeljak, Dragi Kocev, 2011, Journal of environmental quality.

Feature Ranking for Multi-target Regression with Tree Ensemble Methods

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

AiTLAS: Artificial Intelligence Toolbox for Earth Observation

Nikola Simidjievski, Ivan Kitanovski, Ivica Dimitrovski, 2022, Remote. Sens..

Production of Secondary Metabolites in Extreme Environments: Food- and Airborne Wallemia spp. Produce Toxic Metabolites at Hypersaline Conditions

Sašo Džeroski, Dragi Kocev, S. Džeroski, 2016, PloS one.

Ensembles of Multi-Objective Decision Trees

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

Ensembles for Predicting Structured Outputs

Dragi Kocev, D. Kocev, 2012, Informatica.

Ensembles for multi-target regression with random output selections

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

Web genre classification with methods for structured output prediction

Gjorgji Madjarov, Ivica Dimitrovski, Dragi Kocev, 2019, Inf. Sci..

Multi-label Classification Using Random Label Subset Selections

Saso Dzeroski, Martin Breskvar, Dragi Kocev, 2017, DS.

The importance of the label hierarchy in hierarchical multi-label classification

Saso Dzeroski, Dragi Kocev, Jurica Levatic, 2015, Journal of Intelligent Information Systems.

Predictive Clustering Trees for Hierarchical Multi-Target Regression

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

Option predictive clustering trees for multi-target regression

Saso Dzeroski, Dragi Kocev, Aljaz Osojnik, 2020, Computer Science and Information Systems.

Option Predictive Clustering Trees for Hierarchical Multi-label Classification

Saso Dzeroski, Dragi Kocev, Aljaz Osojnik, 2017, DS.

Beam Search Induction and Similarity Constraints for Predictive Clustering Trees

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

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

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

Hierarchical classification of diatom images using ensembles of predictive clustering trees

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

Halophily reloaded: new insights into the extremophilic life-style of Wallemia with the description of Wallemia hederae sp. nov

S. Džeroski, D. Kocev, N. Gunde-Cimerman, 2015, Fungal Diversity.

Non-invasive real-time prediction of inner knee temperatures during therapeutic cooling

Roman Trobec, Dragi Kocev, Aleksandra Rashkovska, 2015, Comput. Methods Programs Biomed..

Semi-supervised regression trees with application to QSAR modelling

Michelangelo Ceci, Sašo Džeroski, Dragi Kocev, 2020, Expert Syst. Appl..

Improved medical image modality classification using a combination of visual and textual features

Sašo Džeroski, Ivan Kitanovski, Ivica Dimitrovski, 2015, Comput. Medical Imaging Graph..

In-Domain Self-Supervised Learning Can Lead to Improvements in Remote Sensing Image Classification

D. Kocev, I. Dimitrovski, N. Simidjievski, 2023, arXiv.org.

Evaluation of Distance Measures for Hierarchical Multi-Label Classification in Functional Genomics

Dragi Kocev, D. Kocev, Darko Aleksovski, 2015 .

Feature ranking for semi-supervised learning pdf

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

Web Genre Classification via Hierarchical Multi-label Classification

Gjorgji Madjarov, Ivica Dimitrovski, Dragi Kocev, 2015, IDEAL.

Feature Extraction for Heartbeat Classification in Single-Lead ECG

A. Rashkovska, J. Bogatinovski, D. Kocev, 2019, 2019 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO).

Performance2vec: a step further in explainable stochastic optimization algorithm performance

Peter Korošec, Tome Eftimov, Dragi Kocev, 2020, GECCO Companion.

Predicting Thermal Power Consumption of the Mars Express Satellite with Machine Learning

Nikola Simidjievski, Martin Breskvar, Dragi Kocev, 2017, 2017 6th International Conference on Space Mission Challenges for Information Technology (SMC-IT).

A Framework for Evaluating Personalized Ranking Systems by Fusing Different Evaluation Measures

Tome Eftimov, Dragi Kocev, Bibek Paudel, 2021, Big Data Res..

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

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

ReliefF for Hierarchical Multi-label Classification

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

DietHub: Dietary habits analysis through understanding the content of recipes

Tome Eftimov, Barbara Koroušić Seljak, Dragi Kocev, 2020 .

Combined chemical genetics and data-driven bioinformatics approach identifies receptor tyrosine kinase inhibitors as host-directed antimicrobials

S. Džeroski, D. Kocev, T. Ottenhoff, 2018, Nature Communications.

Discovering outliers in the Mars Express thermal power consumption patterns pdf

Nikola Simidjievski, Dragi Kocev, Luke Lucas, 2021, 2021 IEEE 8th International Conference on Space Mission Challenges for Information Technology (SMC-IT).

CLUSplus: A decision tree-based framework for predicting structured outputs

S. Džeroski, D. Kocev, Jurica Levatić, 2023, SoftwareX.

Modelling Time-Series of Glucose Measurements from Diabetes Patients Using Predictive Clustering Trees

Saso Dzeroski, Mate Bestek, Andrej Brodnik, 2017, AIME.

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

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

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.

Multivariate Predictive Clustering Trees for Classification

Dragi Kocev, Tomaz Stepisnik, D. Kocev, 2020, ISMIS.

Feature ranking for multi-label classiﬁcation using predictive clustering trees

Sašo Džeroski, Dragi Kocev, S. Džeroski, 2013 .

The use of the label hierarchy in HMC improves performance : A case study in predicting community structure in ecology

Sašo Džeroski, Dragi Kocev, Jurica Levatić, 2013 .

COMPARISON OF DISTANCES FOR MULTI-LABEL CLASSIFICATION WITH PCTs

S. Džeroski, D. Kocev, Valentin Gjorgjioski, 2011 .

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

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

Predictive clustering relates gene annotations to phenotype properties extracted from images

S. Džeroski, D. Kocev, B. Ženko, 2010 .

Predicting gene function using hierarchical multi-label decision tree ensembles

S. Džeroski, D. Kocev, C. Vens, 2010, BMC Bioinformatics.

In-Domain Self-Supervised Learning Improves Remote Sensing Image Scene Classification

D. Kocev, I. Dimitrovski, N. Simidjievski, 2024, IEEE Geoscience and Remote Sensing Letters.

Crop Type Prediction Across Countries and Years: Slovenia, Denmark and the Netherlands

D. Kocev, Žiga Kokalj, I. Dimitrovski, 2022, IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium.

Option Predictive Clustering Trees for Multi-target Regression

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

Machine-learning ready data on the thermal power consumption of the Mars Express Spacecraft

S. Džeroski, D. Kocev, P. Panov, 2022, Scientific Data.

List of Late Breaking Papers accepted for poster presentation at the 17 th International Conference on Discovery Science (DS 2014)

Bidyut Kr. Patra, S. Džeroski, D. Kocev, 2014 .

SYNTHESIS OF OMEGA ZEOLITE

D. Kocev, Blagica Cekova, Elena Kolcakovska, 2004 .

A CONTRIBUTION TO THE SYNTHESIS OF THE LOW-SILICA X ZEOLITE

D. Kocev, Blagica Cekova, Elena Kolcakovska, 2004 .