ASSISTANT 86: A Knowledge-Elicitation Tool for Sophisticated Users. - Bojan Cestnik; Igor Kononenko 001; Ivan Bratko (EWSL, 1987)

Medical Analysis of Automatically Induced Diagnostic Rules. - Vladimir Pirnat; Igor Kononenko 001; T. Janc; Ivan Bratko (AIME, 1989)

Semi-Naive Bayesian Classifier. - Igor Kononenko 001 (EWSL, 1991)

Information-Based Evaluation Criterion for Classifier's Performance. - Igor Kononenko 001; Ivan Bratko (Mach. Learn., 1991)

Combining Decisions of Multiple Rules. - Igor Kononenko 001 (AIMSA, 1992)

Learning as Optimization: Stochastic Generation of Multiple Knowledge. - Igor Kononenko 001; Matevz Kovacic (ML, 1992)

Inductive and Bayesian learning in medical diagnosis. - Igor Kononenko 001 (Appl. Artif. Intell., 1993)

Successive Naive Bayesian Classifier. - Igor Kononenko 001 (Informatica (Slovenia), 1993)

Estimating Attributes: Analysis and Extensions of RELIEF. - Igor Kononenko 001 (ECML, 1994)

On Bayesian Neural Networks. - Igor Kononenko 001 (Informatica (Slovenia), 1994)

Critical Analysis of Rough Sets Approach to Machine Learning. - Igor Kononenko 001; Samo Zorc (Informatica (Slovenia), 1994)

On Biases in Estimating Multi-Valued Attributes. - Igor Kononenko 001 (IJCAI, 1995)

Attribute-Based Learning. - Ivan Bratko; Bojan Cestnik; Igor Kononenko 001 (AI Commun., 1996)

Machine learning in prognosis of the femoral neck fracture recovery. - Matjaz Kukar; Igor Kononenko 001; T. Silvester (Artif. Intell. Medicine, 1996)

On Facts Versus Misconceptions about Rough Sets. - Igor Kononenko 001 (Informatica (Slovenia), 1996)

Machine Learning Applied to Diagnosis of Sport Injuries. - Igor Zelic; Igor Kononenko 001; Nada Lavrac; Vanja Vuga (AIME, 1997)

An application of machine learning in the diagnosis of ischaemic heart disease. - Matjaz Kukar; Ciril Groselj; Igor Kononenko 001; Jure Fettich (CBMS, 1997)

Diagnosis of sport injuries with machine learning: explanation of induced decisions. - Igor Zelic; Igor Kononenko 001; Nada Lavrac; Vanja Vuga (CBMS, 1997)

An adaptation of Relief for attribute estimation in regression. - Marko Robnik-Sikonja; Igor Kononenko 001 (ICML, 1997)

Probabilistic First-Order Classification. - Uros Pompe; Igor Kononenko 001 (ILP, 1997)

Overcoming the Myopia of Inductive Learning Algorithms with RELIEFF. - Igor Kononenko 001; Edvard Simec; Marko Robnik-Sikonja (Appl. Intell., 1997)

Attribute selection for modelling. - Igor Kononenko 001; Se June Hong (Future Gener. Comput. Syst., 1997)

Cost-Sensitive Learning with Neural Networks. - Matjaz Kukar; Igor Kononenko 001 (ECAI, 1998)

Pruning Regression Trees with MDL. - Marko Robnik-Sikonja; Igor Kononenko 001 (ECAI, 1998)

The Minimum Description Length Based Decision Tree Pruning. - Igor Kononenko 001 (PRICAI, 1998)

Efficient Induction and Effective Use of First-Order Knowledge. - Uros Pompe; Igor Kononenko 001 (Appl. Artif. Intell., 1998)

Intelligent Data Analysis for Medical Diagnosis: Using Machine Learning and Temporal Abstraction. - Nada Lavrac; Blaz Zupan; Igor Kononenko 001; Matjaz Kukar; Elpida T. Keravnou (AI Commun., 1998)

Efficient Derivation of the Optimal Assembly Sequence from Product Description. - Samo Zorc; D. Noe; Igor Kononenko 001 (Cybern. Syst., 1998)

Attribute Dependencies, Understandability and Split Selection in Tree Based Models. - Marko Robnik-Sikonja; Igor Kononenko 001 (ICML, 1999)

Analysing and improving the diagnosis of ischaemic heart disease with machine learning. - Matjaz Kukar; Igor Kononenko 001; Ciril Groselj; Katarina Kralj; Jure Fettich (Artif. Intell. Medicine, 1999)

Evaluation of Prognostic Factors and Prediction of Chronic Wound Healing Rate by Machine Learning Tools. - Marko Robnik-Sikonja; David Cukjati; Igor Kononenko 001 (AIME, 2001)

Comprehensible Interpretation of Relief's Estimates. - Marko Robnik-Sikonja; Igor Kononenko 001 (ICML, 2001)

Machine learning for medical diagnosis: history, state of the art and perspective. - Igor Kononenko 001 (Artif. Intell. Medicine, 2001)

A Statistical Approach to Texture Description of Medical Images: A Preliminary Study. - Matjaz Bevk; Igor Kononenko 001 (CBMS, 2002)

Reliable Classifications with Machine Learning. - Matjaz Kukar; Igor Kononenko 001 (ECML, 2002)

Search versus Knowledge: An Empirical Study of Minimax on KRK. - Aleksander Sadikov; Ivan Bratko; Igor Kononenko 001 (ACG, 2003)

Comprehensible evaluation of prognostic factors and prediction of wound healing. - Marko Robnik-Sikonja; David Cukjati; Igor Kononenko 001 (Artif. Intell. Medicine, 2003)

Theoretical and Empirical Analysis of ReliefF and RReliefF. - Marko Robnik-Sikonja; Igor Kononenko 001 (Mach. Learn., 2003)

Automatic Segmentation of Whole-Body Bone Scintigrams as a Preprocessing Step for Computer Assisted Diagnostics. - Luka Sajn; Matjaz Kukar; Igor Kononenko 001; Metka Milcinski (AIME, 2005)

GDV Measures Vitality? - Igor Kononenko 001; Miha Sedej; Aleksander Sadikov (CBMS, 2005)

Estimation of Prediction Reliability in Regression Based on a Transductive Approach. - Zoran Bosnic; Igor Kononenko 001 (IICAI, 2005)

Computerized segmentation of whole-body bone scintigrams and its use in automated diagnostics. - Luka Sajn; Matjaz Kukar; Igor Kononenko 001; Metka Milcinski (Comput. Methods Programs Biomed., 2005)

Bias and pathology in minimax search. - Aleksander Sadikov; Ivan Bratko; Igor Kononenko 001 (Theor. Comput. Sci., 2005)

Towards symbolic mining of images with association rules: Preliminary results on textures. - Matjaz Bevk; Igor Kononenko 001 (Intell. Data Anal., 2006)

Computerized segmentation and diagnostics of whole-body bone scintigrams. - Luka Sajn; Igor Kononenko 001; Metka Milcinski (Comput. Medical Imaging Graph., 2007)

Empirical Analysis of Reliability Estimates for Individual Regression Predictions. - Zoran Bosnic; Igor Kononenko 001 (DaWaK, 2008)

Towards a Model Independent Method for Explaining Classification for Individual Instances. - Erik Strumbelj; Igor Kononenko 001 (DaWaK, 2008)

Estimation of individual prediction reliability using the local sensitivity analysis. - Zoran Bosnic; Igor Kononenko 001 (Appl. Intell., 2008)

Comparison of approaches for estimating reliability of individual regression predictions. - Zoran Bosnic; Igor Kononenko 001 (Data Knowl. Eng., 2008)

Multiresolution Image Parametrization for Improving Texture Classification. - Luka Sajn; Igor Kononenko 001 (EURASIP J. Adv. Signal Process., 2008)

Explaining Classifications For Individual Instances. - Marko Robnik-Sikonja; Igor Kononenko 001 (IEEE Trans. Knowl. Data Eng., 2008)

Learning Betting Tips from Users' Bet Selections. - Erik Strumbelj; Marko Robnik-Sikonja; Igor Kononenko 001 (MLDM, 2009)

Explaining instance classifications with interactions of subsets of feature values. - Erik Strumbelj; Igor Kononenko 001; Marko Robnik-Sikonja (Data Knowl. Eng., 2009)

An overview of advances in reliability estimation of individual predictions in machine learning. - Zoran Bosnic; Igor Kononenko 001 (Intell. Data Anal., 2009)

Extended Symbolic Mining of Textures with Association Rules. - Igor Kononenko 001; Matjaz Bevk (Informatica (Slovenia), 2009)

Influence of Domain and Model Properties on the Reliability Estimates' Performance. - Zoran Bosnic; Igor Kononenko 001 (Int. J. Data Warehous. Min., 2009)

Correction of Regression Predictions Using the Secondary Learner on the Sensitivity Analysis Outputs. - Zoran Bosnic; Igor Kononenko 001 (Comput. Informatics, 2010)

An Efficient Explanation of Individual Classifications using Game Theory. - Erik Strumbelj; Igor Kononenko 001 (J. Mach. Learn. Res., 2010)

Explanation and reliability of prediction models: the case of breast cancer recurrence. - Erik Strumbelj; Zoran Bosnic; Igor Kononenko 001; Branko Zakotnik; Cvetka Grasic Kuhar (Knowl. Inf. Syst., 2010)

Automatic selection of reliability estimates for individual regression predictions. - Zoran Bosnic; Igor Kononenko 001 (Knowl. Eng. Rev., 2010)

Reliability Estimates for Regression Predictions: Performance Analysis. - Zoran Bosnic; Igor Kononenko 001 (Integrations of Data Warehousing, Data Mining and Database Technologies, 2011)

Evaluating Reliability of Single Classifications of Neural Networks. - Darko Pevec; Erik Strumbelj; Igor Kononenko 001 (ICANNGA (1), 2011)

Efficiently Explaining Decisions of Probabilistic RBF Classification Networks. - Marko Robnik-Sikonja; Aristidis Likas; Constantinos Constantinopoulos; Igor Kononenko 001; Erik Strumbelj (ICANNGA (1), 2011)

A General Method for Visualizing and Explaining Black-Box Regression Models. - Erik Strumbelj; Igor Kononenko 001 (ICANNGA (2), 2011)

Correcting Streaming Predictions of an Electricity Load Forecast System Using a Prediction Reliability Estimate. - Zoran Bosnic; Pedro Pereira Rodrigues; Igor Kononenko 001; João Gama 001 (ICMMI, 2011)

Modern parameterization and explanation techniques in diagnostic decision support system: A case study in diagnostics of coronary artery disease. - Matjaz Kukar; Igor Kononenko 001; Ciril Groselj (Artif. Intell. Medicine, 2011)

Model Selection with Combining Valid and Optimal Prediction Intervals. - Darko Pevec; Igor Kononenko 001 (ICDM Workshops, 2012)

Quality of classification explanations with PRBF. - Marko Robnik-Sikonja; Igor Kononenko 001; Erik Strumbelj (Neurocomputing, 2012)

Mining Data From Hemodynamic Simulations for Generating Prediction and Explanation Models. - Zoran Bosnic; Petar Vracar; Milos D. Radovic; Goran Devedzic; Nenad D. Filipovic; Igor Kononenko 001 (IEEE Trans. Inf. Technol. Biomed., 2012)

Multi-level association rules and directed graphs for spatial data analysis. - Boris Petelin; Igor Kononenko 001; Vlado Malacic; Matjaz Kukar (Expert Syst. Appl., 2013)

Efficiently explaining the predictions of a probabilistic radial basis function classification network. - Marko Robnik-Sikonja; Erik Strumbelj; Igor Kononenko 001 (Intell. Data Anal., 2013)

Explanation and Reliability of Individual Predictions. - Igor Kononenko 001; Erik Strumbelj; Zoran Bosnic; Darko Pevec; Matjaz Kukar; Marko Robnik-Sikonja (Informatica (Slovenia), 2013)

Web user profiles with time-decay and prototyping. - Domen Kosir; Igor Kononenko 001; Zoran Bosnic (Appl. Intell., 2014)

Enhancing data stream predictions with reliability estimators and explanation. - Zoran Bosnic; Jaka Demsar; Grega Kespret; Pedro Pereira Rodrigues; João Gama 001; Igor Kononenko 001 (Eng. Appl. Artif. Intell., 2014)

Weighted archetypal analysis of the multi-element graph for query-focused multi-document summarization. - Ercan Canhasi; Igor Kononenko 001 (Expert Syst. Appl., 2014)

Input dependent prediction intervals for supervised regression. - Darko Pevec; Igor Kononenko 001 (Intell. Data Anal., 2014)

Visualization and Concept Drift Detection Using Explanations of Incremental Models. - Janez Demsar; Zoran Bosnic; Igor Kononenko 001 (Informatica (Slovenia), 2014)

Multi-document summarization via Archetypal Analysis of the content-graph joint model. - Ercan Canhasi; Igor Kononenko 001 (Knowl. Inf. Syst., 2014)

Explaining prediction models and individual predictions with feature contributions. - Erik Strumbelj; Igor Kononenko 001 (Knowl. Inf. Syst., 2014)

Learning from depth sensor data using inductive logic programming. - Miha Drole; Petar Vracar; Ante Panjkota; Ivo Stancic; Josip Music; Igor Kononenko 001; Matjaz Kukar (ICAT, 2015)

Prediction intervals in supervised learning for model evaluation and discrimination. - Darko Pevec; Igor Kononenko 001 (Appl. Intell., 2015)

Dynamic fuzzy paths and cycles in multi-level directed graphs. - Boris Petelin; Igor Kononenko 001; Vlado Malacic; Matjaz Kukar (Eng. Appl. Artif. Intell., 2015)

Obtaining structural descriptions of building façades. - Petar Vracar; Igor Kononenko 001; Marko Robnik-Sikonja (Comput. Sci. Inf. Syst., 2016)

Weighted hierarchical archetypal analysis for multi-document summarization. - Ercan Canhasi; Igor Kononenko 001 (Comput. Speech Lang., 2016)

Modeling basketball play-by-play data. - Petar Vracar; Erik Strumbelj; Igor Kononenko 001 (Expert Syst. Appl., 2016)

Closed world specialisation inside the induction process. - Miha Drole; Igor Kononenko 001 (Intell. Data Anal., 2016)

Pairwise saturations in inductive logic programming. - Miha Drole; Igor Kononenko 001 (Artif. Intell. Rev., 2017)

Early Machine Learning Research in Ljubljana. - Igor Kononenko 001 (Informatica (Slovenia), 2018)

Explaining the Predictions of an Arbitrary Prediction Model: Feature Contributions and Quasi-nomograms. - Erik Strumbelj; Igor Kononenko 001 (Human and Machine Learning, 2018)

Frequent subgraph mining in oceanographic multi-level directed graphs. - Boris Petelin; Igor Kononenko 001; Vlado Malacic; Matjaz Kukar (Int. J. Geogr. Inf. Sci., 2019)

Automatic attribute construction for basketball modelling. - Petar Vracar; Erik Strumbelj; Igor Kononenko 001 (Knowl. Inf. Syst., 2020)

SuperFormer: Continual learning superposition method for text classification. - Marko Zeman; Jana Faganeli Pucer; Igor Kononenko 001; Zoran Bosnic (Neural Networks, 2023)

Conditional generative positive and unlabeled learning. - Ales Papic; Igor Kononenko 001; Zoran Bosnic (Expert Syst. Appl., 2023)

Analysis of neuropsychological and neuroradiological features for diagnosis of Alzheimer's disease and mild cognitive impairment. - Vladimir Kurbalija; Zoltan Geler; Tijana Vujanic Stankov; Igor Petrusic; Mirjana Ivanovic; Igor Kononenko 001; Marija Semnic; Marko Dakovic; Robert Semnic; Zoran Bosnic (Int. J. Medical Informatics, 2023)