B. Ženko

发表

Social activity modelling and multimodal coaching for active aging

Bernard Zenko, Martin Znidarsic, Richard Wheeler, 2019, PETRA.

Homogeneous clusters of Alzheimer’s disease patient population

Dragan Gamberger, Nada Lavrač, Alexis Mitelpunkt, 2016, Biomedical engineering online.

Yeasts and yeast-like fungi in tap water and groundwater, and their transmission to household appliances

S. Džeroski, N. Gunde-Cimerman, B. Ženko, 2016 .

Exploratory clustering for patient subpopulation discovery

N. Lavrac, D. Gamberger, B. Ženko, 2017 .

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

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

Authentication of key aroma compounds in apple using stable isotope approach.

M. Bohanec, M. Žnidaršič, M. Luštrek, 2019, Food chemistry.

A comparison of stacking with meta decision trees to other combining methods

Ljupčo Todorovski, Bernard Ženko, L. Todorovski, 2001 .

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.

Neuroblastoma tumorigenesis is regulated through the Nm23-H1/h-Prune C-terminal interaction

S. Džeroski, F. Westermann, B. Ženko, 2013, Scientific Reports.

Speeding-Up Hoeffding-Based Regression Trees With Options

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

Learning Predictive Clustering Rules

Bernard Ženko, B. Ženko, 2005, Informatica.

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.

A comparison of stacking with MDTs to bagging, boosting, and other stacking methods

Ljupčo Todorovski, Bernard Ženko, L. Todorovski, 2001 .

Candida and Fusarium species known as opportunistic human pathogens from customer-accessible parts of residential washing machines.

S. Džeroski, N. Gunde-Cimerman, B. Ženko, 2015, Fungal biology.

Changes of poultry faecal microbiota associated with Clostridium difficile colonisation.

S. Džeroski, B. Ženko, M. Rupnik, 2013, Veterinary microbiology.

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

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

Modelling forest growing stock from inventory data: A data mining approach

Marko Debeljak, Bernard Ženko, Aleš Poljanec, 2014 .

Is Combining Classifiers Better than Selecting the Best One

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

Stacking with Multi-response Model Trees

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

Multi-target regression with rule ensembles

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

MetaBags: Bagged Meta-Decision Trees for Regression

Saso Dzeroski, Ammar Shaker, Luís Moreira-Matias, 2018, ECML/PKDD.

Gut Microbiota Patterns Associated with Colonization of Different Clostridium difficile Ribotypes

Bernard Zenko, Saso Dzeroski, Domen Mongus, 2013, PloS one.

Decoupling approximation robustly reconstructs directed dynamical networks pdf

Zoran Levnajic, Bernard Zenko, Saso Dzeroski, 2017, New Journal of Physics.

Machine Learning, Ensemble Methods in

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

EditorialThe Fourth International Workshop on Environmental Applications of Machine Learning, 27 September–1 October 2004, Bled, Slovenia

Sašo Džeroski, Marko Debeljak, Bernard Ženko, 2006 .

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

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

Estimating the risk of fire outbreaks in the natural environment

Bernard Zenko, Saso Dzeroski, Daniela Stojanova, 2012, Data Mining and Knowledge Discovery.

Multi-criteria Modelling Approach for Ambient Assisted Coaching of Senior Adults

Zlatko Matjacic, Marko Bohanec, Martin Znidarsic, 2019, KEOD.

Clusters of male and female Alzheimer’s disease patients in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database

D. Gamberger, B. Ženko, Alexis Mitelpunkt, 2016, Brain Informatics.

Identification of Gender Specific Biomarkers for Alzheimer's Disease

Bernard Zenko, Nada Lavrac, Dragan Gamberger, 2015, BIH.

Multilayer Clustering: Biomarker Driven Segmentation of Alzheimer's Disease Patient Population

Bernard Zenko, Nada Lavrac, Dragan Gamberger, 2015, IWBBIO.

Personality Traits in Miners with Past Occupational Elemental Mercury Exposure

S. Džeroski, B. Ženko, J. Osredkar, 2006, Environmental health perspectives.

Homogeneous clusters of Alzheimer’s disease patient population

D. Gamberger, B. Ženko, Alexis Mitelpunkt, 2016, Biomedical engineering online.

Relating personality traits and mercury exposure in miners with machine learning methods

Bernard Zenko, Saso Dzeroski, Darja Kobal Grum, 2004, EnviroInfo.

Evaluation Method for Feature Rankings and their Aggregations for Biomarker Discovery

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

Reconstructing dynamical networks via feature ranking

Zoran Levnajic, Bernard Zenko, Ljupco Todorovski, 2019, Chaos.

Improving Effectiveness of a Coaching System Through Preference Learning

Bernard Zenko, Martin Znidarsic, Aljaz Osojnik, 2021, PETRA.

Rule Ensembles for Multi-target Regression

Timo Aho, Bernard Zenko, Saso Dzeroski, 2009, 2009 Ninth IEEE International Conference on Data Mining.

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).

Other Advanced Research Initiatives in Elderly Care and Fragility Prevention

Dimitrios A. Gatsios, D. Fotiadis, G. Cordasco, 2021, Digital Health Technology for Better Aging.

Predictive clustering relates gene annotations to phenotype properties extracted from images

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

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

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

Machine Learning, Ensemble Methods in

S. Džeroski, P. Panov, B. Ženko, 2009, Encyclopedia of Complexity and Systems Science.

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

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