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Igor Kononenko
2010 – today
- 2013
[j36]B. Petelin, Igor Kononenko, V. Malacic, Matjaz Kukar: Multi-level association rules and directed graphs for spatial data analysis. Expert Syst. Appl. 40(12): 4957-4970 (2013)- 2012
- [j35]Marko Robnik-Sikonja, Igor Kononenko, Erik Strumbelj: Quality of classification explanations with PRBF. Neurocomputing 96: 37-46 (2012)
- [j34]Zoran Bosnic, Petar Vracar, Milos D. Radovic, Goran Devedzic, Nenad D. Filipovic, Igor Kononenko: Mining Data From Hemodynamic Simulations for Generating Prediction and Explanation Models. IEEE Transactions on Information Technology in Biomedicine 16(2): 248-254 (2012)
- [c31]Darko Pevec, Igor Kononenko: Model Selection with Combining Valid and Optimal Prediction Intervals. ICDM Workshops 2012: 653-658
- 2011
- [j33]Matjaz Kukar, Igor Kononenko, Ciril Groselj: Modern parameterization and explanation techniques in diagnostic decision support system: A case study in diagnostics of coronary artery disease. Artificial Intelligence in Medicine 52(2): 77-90 (2011)
- [p1]Zoran Bosnic, Igor Kononenko: Reliability Estimates for Regression Predictions: Performance Analysis. Integrations of Data Warehousing, Data Mining and Database Technologies 2011: 320-338
- [c30]Erik Strumbelj, Igor Kononenko: A General Method for Visualizing and Explaining Black-Box Regression Models. ICANNGA (2) 2011: 21-30
- [c29]Darko Pevec, Erik Strumbelj, Igor Kononenko: Evaluating Reliability of Single Classifications of Neural Networks. ICANNGA (1) 2011: 22-30
- [c28]Marko Robnik-Sikonja, Aristidis Likas, Constantinos Constantinopoulos, Igor Kononenko, Erik Strumbelj: Efficiently Explaining Decisions of Probabilistic RBF Classification Networks. ICANNGA (1) 2011: 169-179
- 2010
- [j32]Zoran Bosnic, Igor Kononenko: Correction of Regression Predictions Using the Secondary Learner on the Sensitivity Analysis Outputs. Computing and Informatics 29(6): 929-946 (2010)
- [j31]Erik Strumbelj, Igor Kononenko: An Efficient Explanation of Individual Classifications using Game Theory. Journal of Machine Learning Research 11: 1-18 (2010)
- [j30]Erik Strumbelj, Zoran Bosnic, Igor Kononenko, Branko Zakotnik, Cvetka Grasic Kuhar: Explanation and reliability of prediction models: the case of breast cancer recurrence. Knowl. Inf. Syst. 24(2): 305-324 (2010)
- [j29]Zoran Bosnic, Igor Kononenko: Automatic selection of reliability estimates for individual regression predictions. Knowledge Eng. Review 25(1): 27-47 (2010)
2000 – 2009
- 2009
- [j28]Erik Strumbelj, Igor Kononenko, Marko Robnik-Sikonja: Explaining instance classifications with interactions of subsets of feature values. Data Knowl. Eng. 68(10): 886-904 (2009)
- [j27]Zoran Bosnic, Igor Kononenko: An overview of advances in reliability estimation of individual predictions in machine learning. Intell. Data Anal. 13(2): 385-401 (2009)
- [j26]Igor Kononenko, Matjaz Bevk: Extended Symbolic Mining of Textures with Association Rules. Informatica (Slovenia) 33(4): 487-497 (2009)
- [j25]Zoran Bosnic, Igor Kononenko: Influence of Domain and Model Properties on the Reliability Estimates' Performance. IJDWM 5(4): 58-76 (2009)
- [c27]Erik Strumbelj, Marko Robnik-Sikonja, Igor Kononenko: Learning Betting Tips from Users' Bet Selections. MLDM 2009: 678-688
- 2008
- [j24]Zoran Bosnic, Igor Kononenko: Estimation of individual prediction reliability using the local sensitivity analysis. Appl. Intell. 29(3): 187-203 (2008)
- [j23]Zoran Bosnic, Igor Kononenko: Comparison of approaches for estimating reliability of individual regression predictions. Data Knowl. Eng. 67(3): 504-516 (2008)
- [j22]Luka Sajn, Igor Kononenko: Multiresolution Image Parametrization for Improving Texture Classification. EURASIP J. Adv. Sig. Proc. 2008 (2008)
- [j21]Marko Robnik-Sikonja, Igor Kononenko: Explaining Classifications For Individual Instances. IEEE Trans. Knowl. Data Eng. 20(5): 589-600 (2008)
- [c26]Erik Strumbelj, Igor Kononenko: Towards a Model Independent Method for Explaining Classification for Individual Instances. DaWaK 2008: 273-282
- [c25]Zoran Bosnic, Igor Kononenko: Empirical Analysis of Reliability Estimates for Individual Regression Predictions. DaWaK 2008: 379-388
- 2007
- [j20]Luka Sajn, Igor Kononenko, Metka Milcinski: Computerized segmentation and diagnostics of whole-body bone scintigrams. Comp. Med. Imag. and Graph. 31(7): 531-541 (2007)
- 2006
- [j19]Matjaz Bevk, Igor Kononenko: Towards symbolic mining of images with association rules: Preliminary results on textures. Intell. Data Anal. 10(4): 379-393 (2006)
- 2005
- [j18]Luka Sajn, Matjaz Kukar, Igor Kononenko, Metka Milcinski: Computerized segmentation of whole-body bone scintigrams and its use in automated diagnostics. Computer Methods and Programs in Biomedicine 80(1): 47-55 (2005)
- [j17]Aleksander Sadikov, Ivan Bratko, Igor Kononenko: Bias and pathology in minimax search. Theor. Comput. Sci. 349(2): 268-281 (2005)
- [c24]Luka Sajn, Matjaz Kukar, Igor Kononenko, Metka Milcinski: Automatic Segmentation of Whole-Body Bone Scintigrams as a Preprocessing Step for Computer Assisted Diagnostics. AIME 2005: 363-372
- [c23]
- [c22]Zoran Bosnic, Igor Kononenko: Estimation of Prediction Reliability in Regression Based on a Transductive Approach. IICAI 2005: 3502-3516
- 2003
- [j16]Marko Robnik-Sikonja, David Cukjati, Igor Kononenko: Comprehensible evaluation of prognostic factors and prediction of wound healing. Artificial Intelligence in Medicine 29(1-2): 25-38 (2003)
- [j15]Marko Robnik-Sikonja, Igor Kononenko: Theoretical and Empirical Analysis of ReliefF and RReliefF. Machine Learning 53(1-2): 23-69 (2003)
- [c21]Aleksander Sadikov, Ivan Bratko, Igor Kononenko: Search versus Knowledge: An Empirical Study of Minimax on KRK. ACG 2003: 33-44
- 2002
- [c20]Matjaz Bevk, Igor Kononenko: A Statistical Approach to Texture Description of Medical Images: A Preliminary Study. CBMS 2002: 239-240
- [c19]
- 2001
- [j14]Igor Kononenko: Machine learning for medical diagnosis: history, state of the art and perspective. Artificial Intelligence in Medicine 23(1): 89-109 (2001)
- [c18]Marko Robnik-Sikonja, David Cukjati, Igor Kononenko: Evaluation of Prognostic Factors and Prediction of Chronic Wound Healing Rate by Machine Learning Tools. AIME 2001: 77-87
- [c17]Marko Robnik-Sikonja, Igor Kononenko: Comprehensible Interpretation of Relief's Estimates. ICML 2001: 433-440
1990 – 1999
- 1999
- [j13]Matjaz Kukar, Igor Kononenko, Ciril Groselj, Katarina Kralj, Jure Fettich: Analysing and improving the diagnosis of ischaemic heart disease with machine learning. Artificial Intelligence in Medicine 16(1): 25-50 (1999)
- [c16]Marko Robnik-Sikonja, Igor Kononenko: Attribute Dependencies, Understandability and Split Selection in Tree Based Models. ICML 1999: 344-353
- 1998
- [j12]Uros Pompe, Igor Kononenko: Efficient Induction and Effective Use of First-Order Knowledge. Applied Artificial Intelligence 12(5): 421-453 (1998)
- [j11]Nada Lavrac, Blaz Zupan, Igor Kononenko, Matjaz Kukar, Elpida T. Keravnou: Intelligent Data Analysis for Medical Diagnosis: Using Machine Learning and Temporal Abstraction. AI Commun. 11(3-4): 191-218 (1998)
- [j10]Samo Zorc, D. Noe, Igor Kononenko: Efficient Derivation of the Optimal Assembly Sequence from Product Description. Cybernetics and Systems 29(2): 159-179 (1998)
- [c15]
- [c14]
- [c13]
- 1997
- [j9]Igor Kononenko, Edvard Simec, Marko Robnik-Sikonja: Overcoming the Myopia of Inductive Learning Algorithms with RELIEFF. Appl. Intell. 7(1): 39-55 (1997)
- [c12]Igor Zelic, Igor Kononenko, Nada Lavrac, Vanja Vuga: Machine Learning Applied to Diagnosis of Sport Injuries. AIME 1997: 138-141
- [c11]Matjaz Kukar, Ciril Groselj, Igor Kononenko, Jure Fettich: An Application of Machine Learning in the Diagnosis of Ischaemic Heart Disease. AIME 1997: 461-464
- [c10]Matjaz Kukar, Ciril Groselj, Igor Kononenko, Jure Fettich: An application of machine learning in the diagnosis of ischaemic heart disease. CBMS 1997: 70-75
- [c9]Igor Zelic, Igor Kononenko, Nada Lavrac, Vanja Vuga: Diagnosis of sport injuries with machine learning: explanation of induced decisions. CBMS 1997: 195-199
- [c8]Marko Robnik-Sikonja, Igor Kononenko: An adaptation of Relief for attribute estimation in regression. ICML 1997: 296-304
- [c7]
- 1996
- [j8]
- [j7]Matjaz Kukar, Igor Kononenko, T. Silvester: Machine learning in prognosis of the femoral neck fracture recovery. Artificial Intelligence in Medicine 8(5): 431-451 (1996)
- [j6]Igor Kononenko: On Facts Versus Misconceptions about Rough Sets. Informatica (Slovenia) 20(4) (1996)
- 1995
- [c6]
- 1994
- [j5]
- [j4]Igor Kononenko, Samo Zorc: Critical Analysis of Rough Sets Approach to Machine Learning. Informatica (Slovenia) 18(3) (1994)
- [c5]
- 1993
- [j3]Igor Kononenko: Inductive and Bayesian learning in medical diagnosis. Applied Artificial Intelligence 7(4): 317-337 (1993)
- [j2]
- 1992
- [c4]
- [c3]Igor Kononenko, Matevz Kovacic: Learning as Optimization: Stochastic Generation of Multiple Knowledge. ML 1992: 257-262
- 1991
- [j1]Igor Kononenko, Ivan Bratko: Information-Based Evaluation Criterion for Classifier's Performance. Machine Learning 6: 67-80 (1991)
- [c2]
1980 – 1989
- 1987
- [c1]Bojan Cestnik, Igor Kononenko, Ivan Bratko: ASSISTANT 86: A Knowledge-Elicitation Tool for Sophisticated Users. EWSL 1987: 31-45
Coauthor Index
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last updated on 2013-05-08 22:57 CEST by the dblp team