 | 2012 |
| 49 |  | Sotiris B. Kotsiantis:
Use of machine learning techniques for educational proposes: a decision support system for forecasting students' grades.
Artif. Intell. Rev. 37(4): 331-344 (2012) |
| 2011 |
| 48 |  | Sotiris B. Kotsiantis:
Combining bagging, boosting, rotation forest and random subspace methods.
Artif. Intell. Rev. 35(3): 223-240 (2011) |
| 47 |  | Sotiris B. Kotsiantis:
An incremental ensemble of classifiers.
Artif. Intell. Rev. 36(4): 249-266 (2011) |
| 46 |  | Sotiris B. Kotsiantis:
Cascade Generalization with Reweighting Data for Handling Imbalanced Problems.
Comput. J. 54(9): 1547-1559 (2011) |
| 45 |  | Sotiris B. Kotsiantis:
A random subspace method that uses different instead of similar models for regression and classification problems.
IJIDS 3(2): 173-188 (2011) |
| 2010 |
| 44 |  | Sotiris B. Kotsiantis,
Dimitris N. Kanellopoulos:
Bagging different instead of similar models for regression and classification problems.
IJCAT 37(1): 20-28 (2010) |
| 43 |  | Sotiris B. Kotsiantis,
Dimitris Kanellopoulos,
Vasilis Tampakas:
Financial Application of Multi-Instance Learning: Two Greek Case Studies.
JCIT 5(8): 42-53 (2010) |
| 42 |  | Sotiris B. Kotsiantis,
Kiriakos Patriarcheas,
Michalis Nik Xenos:
A combinational incremental ensemble of classifiers as a technique for predicting students' performance in distance education.
Knowl.-Based Syst. 23(6): 529-535 (2010) |
| 2009 |
| 41 |  | Sotiris B. Kotsiantis:
Locally application of random subspace with simple Bayesian classifier.
IJDMMM 1(4): 375-392 (2009) |
| 40 |  | Sotiris B. Kotsiantis:
Educational data mining: a case study for predicting dropout-prone students.
IJKESDP 1(2): 101-111 (2009) |
| 39 |  | Sotiris B. Kotsiantis,
Panayiotis E. Pintelas:
Selective costing ensemble for handling imbalanced data sets.
Int. J. Hybrid Intell. Syst. 6(3): 123-133 (2009) |
| 2008 |
| 38 |  | Sotiris B. Kotsiantis,
Dimitris Kanellopoulos:
Applying Machine Learning Techniques for Environmental Reporting.
NCM (1) 2008: 217-223 |
| 37 |  | Sotiris B. Kotsiantis:
Local Grading of Learners.
Panhellenic Conference on Informatics 2008: 209-213 |
| 36 |  | Sotiris B. Kotsiantis:
Stacking Cost Sensitive Models.
Panhellenic Conference on Informatics 2008: 217-221 |
| 35 |  | Sotiris B. Kotsiantis:
Handling imbalanced data sets with a modification of Decorate algorithm.
IJCAT 33(2/3): 91-98 (2008) |
| 34 |  | Sotiris B. Kotsiantis:
Locally application of cascade generalization for classification problems.
Intelligent Decision Technologies 2(4): 239-246 (2008) |
| 2007 |
| 33 |  | D. Anyfantis,
M. Karagiannopoulos,
Sotiris B. Kotsiantis,
Panayiotis E. Pintelas:
Robustness of learning techniques in handling class noise in imbalanced datasets.
AIAI 2007: 21-28 |
| 32 |  | M. Karagiannopoulos,
D. Anyfantis,
Sotiris B. Kotsiantis,
Panayiotis E. Pintelas:
A Wrapper for Reweighting Training Instances for Handling Imbalanced Data Sets.
AIAI 2007: 29-36 |
| 31 |  | Sotiris B. Kotsiantis,
Dimitris Kanellopoulos:
Combining Bagging, Boosting and Dagging for Classification Problems.
KES (2) 2007: 493-500 |
| 30 |  | Sotiris B. Kotsiantis:
Supervised Machine Learning: A Review of Classification Techniques.
Emerging Artificial Intelligence Applications in Computer Engineering 2007: 3-24 |
| 29 |  | Sotiris B. Kotsiantis:
Credit risk analysis using a hybrid data mining model.
IJISTA 2(4): 345-356 (2007) |
| 28 |  | Sotiris B. Kotsiantis:
Supervised Machine Learning: A Review of Classification Techniques.
Informatica (Slovenia) 31(3): 249-268 (2007) |
| 27 |  | Sotiris B. Kotsiantis,
Dimitris Tzelepis,
Euaggelos Koumanakos,
Vasilis Tampakas:
Selective costing voting for bankruptcy prediction.
KES Journal 11(2): 115-127 (2007) |
| 2006 |
| 26 |  | Sotiris B. Kotsiantis:
Local Ordinal Classification.
AIAI 2006: 1-8 |
| 25 |  | Sotiris B. Kotsiantis,
Dimitris Kanellopoulos,
Ioannis D. Zaharakis:
Bagged Averaging of Regression Models.
AIAI 2006: 53-60 |
| 24 |  | Dimitris Kanellopoulos,
Sotiris B. Kotsiantis,
Panayiotis E. Pintelas:
Ontology-based Learning Applications: A Development Methodology.
IASTED Conf. on Software Engineering 2006: 27-32 |
| 23 |  | Sotiris B. Kotsiantis,
Euaggelos Koumanakos,
Dimitris Tzelepis,
Vasilis Tampakas:
Financial Application of Neural Networks: Two Case Studies in Greece.
ICANN (2) 2006: 672-681 |
| 22 |  | Sotiris B. Kotsiantis,
Dimitris Kanellopoulos,
Panayiotis E. Pintelas:
Local Additive Regression of Decision Stumps.
SETN 2006: 148-157 |
| 21 |  | Sotiris B. Kotsiantis,
Euaggelos Koumanakos,
Dimitris Tzelepis,
Vasilis Tampakas:
Predicting Fraudulent Financial Statements with Machine Learning Techniques.
SETN 2006: 538-542 |
| 20 |  | Sotiris B. Kotsiantis,
Ioannis D. Zaharakis,
Panayiotis E. Pintelas:
Machine learning: a review of classification and combining techniques.
Artif. Intell. Rev. 26(3): 159-190 (2006) |
| 19 |  | Sotiris B. Kotsiantis:
Local averaging of heterogeneous regression models.
Int. J. Hybrid Intell. Syst. 3(2): 99-107 (2006) |
| 18 |  | Sotiris B. Kotsiantis,
Dimitris Kanellopoulos,
Panayiotis E. Pintelas:
Local Boosting of Decision Stumps for Regression and Classification Problems.
JCP 1(4): 30-37 (2006) |
| 2005 |
| 17 |  | Sotiris B. Kotsiantis,
Panayiotis E. Pintelas:
Predicting Students' Marks in Hellenic Open University.
ICALT 2005: 664-668 |
| 16 |  | Sotiris B. Kotsiantis,
George E. Tsekouras,
Panayiotis E. Pintelas:
Local Bagging of Decision Stumps.
IEA/AIE 2005: 406-411 |
| 15 |  | George E. Tsekouras,
Dimitris Papageorgiou,
Sotiris B. Kotsiantis,
Christos Kalloniatis,
Panayiotis E. Pintelas:
A Fuzzy Logic-Based Approach for Detecting Shifting Patterns in Cross-Cultural Data.
IEA/AIE 2005: 705-708 |
| 14 |  | Sotiris B. Kotsiantis,
George E. Tsekouras,
C. Raptis,
Panayiotis E. Pintelas:
Modeling the Organoleptic Properties of Matured Wine Distillates.
MLDM 2005: 667-673 |
| 13 |  | Sotiris B. Kotsiantis,
George E. Tsekouras,
Panayiotis E. Pintelas:
Bagging Random Trees for Estimation of Tissue Softness.
MLDM 2005: 674-681 |
| 12 |  | Sotiris B. Kotsiantis,
George E. Tsekouras,
Panayiotis E. Pintelas:
Bagging Model Trees for Classification Problems.
Panhellenic Conference on Informatics 2005: 328-337 |
| 11 |  | Sotiris B. Kotsiantis,
Panayiotis E. Pintelas:
Logitboost of Simple Bayesian Classifier.
Informatica (Slovenia) 29(1): 53-60 (2005) |
| 10 |  | Sotiris B. Kotsiantis,
Panayiotis E. Pintelas:
Local voting of weak classifiers.
KES Journal 9(3): 239-248 (2005) |
| 2004 |
| 9 |  | Sotiris B. Kotsiantis,
Panayiotis E. Pintelas:
Bagged Voting Ensembles.
AIMSA 2004: 168-177 |
| 8 |  | Sotiris B. Kotsiantis,
Panayiotis E. Pintelas:
Increasing the Classification Accuracy of Simple Bayesian Classifier.
AIMSA 2004: 198-207 |
| 7 |  | Sotiris B. Kotsiantis,
Panayiotis E. Pintelas:
A Hybrid Decision Support Tool - Using Ensemble of Classifiers.
ICEIS (2) 2004: 448-456 |
| 6 |  | George E. Tsekouras,
Dimitris Papageorgiou,
Sotiris B. Kotsiantis,
Christos Kalloniatis,
Panayiotis E. Pintelas:
Fuzzy Clustering of Categorical Attributes and its Use in Analyzing Cultural Data.
International Conference on Computational Intelligence 2004: 202-206 |
| 5 |  | Sotiris B. Kotsiantis,
Panayiotis E. Pintelas:
An Online Ensemble of Classifiers.
PRIS 2004: 59-68 |
| 4 |  | Sotiris B. Kotsiantis,
Panayiotis E. Pintelas:
A Cost Sensitive Technique for Ordinal Classification Problems.
SETN 2004: 220-229 |
| 3 |  | Sotiris B. Kotsiantis,
Christos Pierrakeas,
Panayiotis E. Pintelas:
Predicting Students' Performance In Distance Learning Using Machine Learning Techniques.
Applied Artificial Intelligence 18(5): 411-426 (2004) |
| 2 |  | Sotiris B. Kotsiantis,
Panayiotis E. Pintelas:
A decision support prototype tool for predicting student performance in an ODL environment.
Interact. Techn. Smart Edu. 1(4): 253-264 (2004) |
| 2003 |
| 1 |  | Sotiris B. Kotsiantis,
Christos Pierrakeas,
Panayiotis E. Pintelas:
Preventing Student Dropout in Distance Learning Using Machine Learning Techniques.
KES 2003: 267-274 |