2023 - Research.com Computer Science in Slovenia Leader Award
2022 - Research.com Computer Science in Slovenia Leader Award
2016 - Member of Academia Europaea
Sašo Džeroski mainly focuses on Artificial intelligence, Machine learning, Decision tree, Inductive logic programming and Random forest. He mostly deals with Knowledge extraction in his studies of Artificial intelligence. His Machine learning research is multidisciplinary, incorporating elements of Tree, Set, Gene and Pattern recognition.
Decision tree is a subfield of Data mining that he tackles. The study incorporates disciplines such as Relational database, Theoretical computer science, Logic programming and Inductive programming in addition to Inductive logic programming. His Random forest study integrates concerns from other disciplines, such as Interpretation, Proper linear model, Regression, Ensemble learning and Simple.
His primary scientific interests are in Artificial intelligence, Machine learning, Data mining, Cluster analysis and Decision tree. His Artificial intelligence research incorporates elements of Tree and Pattern recognition. The concepts of his Machine learning study are interwoven with issues in Classifier, Hierarchy and Regression.
His research in Data mining intersects with topics in Structure, Set and Benchmark. His biological study spans a wide range of topics, including Feature ranking and Automatic image annotation. His Inductive logic programming study incorporates themes from Inductive programming, Logic programming and Statistical relational learning.
Sašo Džeroski mostly deals with Artificial intelligence, Machine learning, Cluster analysis, Feature ranking and Pattern recognition. His Artificial intelligence study integrates concerns from other disciplines, such as Tree and Extension. His research integrates issues of Classifier, Free parameter and Regression in his study of Machine learning.
He focuses mostly in the field of Regression, narrowing it down to matters related to Supervised learning and, in some cases, Set. His studies in Cluster analysis integrate themes in fields like Transfer of learning, Gene expression, Gene regulatory network and Overfitting. His work investigates the relationship between Feature ranking and topics such as Benchmark that intersect with problems in Synthetic data and Data mining.
Sašo Džeroski focuses on Artificial intelligence, Machine learning, Artificial neural network, Set and Foot. His Artificial intelligence research includes elements of Tree and Pattern recognition. His Decision tree learning study, which is part of a larger body of work in Machine learning, is frequently linked to Subject-matter expert, bridging the gap between disciplines.
His work deals with themes such as Random forest, Mutual information and Feature, which intersect with Artificial neural network. The Set study combines topics in areas such as Annotation, Relation, Cheminformatics and Identification. His study of Foot brings together topics like Heel, Statistics, 3d scanning, Grading and Single group.
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Inductive Logic Programming: Techniques and Applications
Nada Lavrac;Saso Dzeroski.
Relational Data Mining
Saso Dzeroski;Nada Lavrac.
A large-scale evaluation of computational protein function prediction
Predrag Radivojac;Wyatt T Clark;Tal Ronnen Oron;Alexandra M Schnoes.
Nature Methods (2013)
Is Combining Classifiers with Stacking Better than Selecting the Best One
Saso Džeroski;Bernard Ženko.
Machine Learning (2004)
Decision trees for hierarchical multi-label classification
Celine Vens;Jan Struyf;Leander Schietgat;Sašo Džeroski.
Machine Learning (2008)
The MONK's problems: A Performance Comparison of Different Learning Algorithms
Sebastian B. Thrun;Jerzy W. Bala;Eric Bloedorn;Ivan Bratko.
Relational reinforcement learning
Sašo Džeroski;Luc De Raedt;Kurt Driessens.
Machine Learning (2001)
Multi-relational data mining: an introduction
Sigkdd Explorations (2003)
Learning model trees from evolving data streams
Elena Ikonomovska;João Gama;Sašo Džeroski.
Data Mining and Knowledge Discovery (2011)
Learning nonrecursive definitions of relations with LINUS
Nada Lavrač;Sašo Džeroski;Marko Grobelnik.
EWSL'91 Proceedings of the 5th European Conference on European Working Session on Learning (1991)
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