Sotiris B. Kotsiantis

88 papers B 2C 8Misc 9Journal 43Unranked 25

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	kNN Classification: a review. Ann. Math. Artif. Intell. Panos K. Syriopoulos, Nektarios G. Kalampalikis, Sotiris B. Kotsiantis, Michael N. Vrahatis
2023	J	`jnl`	Novel Sparse Feature Regression Method for Traffic Forecasting. Int. J. Artif. Intell. Tools Athanasios I. Salamanis, George A. Gravvanis, Sotiris B. Kotsiantis, Michael N. Vrahatis
2022	J	`jnl`	Rotation forest of random subspace models. Intell. Decis. Technol. Stamatios-Aggelos N. Alexandropoulos, Christos K. Aridas, Sotiris B. Kotsiantis, George A. Gravvanis, Michael N. Vrahatis
2022	—	`conf`	Survey on KNN Methods in Data Science. LION Panos K. Syriopoulos, Sotiris B. Kotsiantis, Michael N. Vrahatis
2020	—	`conf`	Active Hidden Naive Bayes. PCI Vangjel Kazllarof, Sotiris B. Kotsiantis
2020	J	`jnl`	Uncertainty Based Under-Sampling for Learning Naive Bayes Classifiers Under Imbalanced Data Sets. IEEE Access Christos K. Aridas, Stamatis Karlos, Vasileios G. Kanas, Nikos Fazakis, Sotiris B. Kotsiantis
2019	C	`conf`	A Deep Dense Neural Network for Bankruptcy Prediction. EANN Stamatios-Aggelos N. Alexandropoulos, Christos K. Aridas, Sotiris B. Kotsiantis, Michael N. Vrahatis
2019	J	`jnl`	Data preprocessing in predictive data mining. Knowl. Eng. Rev. Stamatios-Aggelos N. Alexandropoulos, Sotiris B. Kotsiantis, Michael N. Vrahatis
2019	—	`conf`	Financial Fraudulent Statements Detection through a Deep Dense Artificial Neural Network. IISA Georgios S. Temponeras, Stamatios-Aggelos N. Alexandropoulos, Sotiris B. Kotsiantis, Michael N. Vrahatis
2019	J	`jnl`	Hybrid local boosting utilizing unlabeled data in classification tasks. Evol. Syst. Christos K. Aridas, Sotiris B. Kotsiantis, Michael N. Vrahatis
2019	Misc	`conf`	Stacking Strong Ensembles of Classifiers. AIAI Stamatios-Aggelos N. Alexandropoulos, Christos K. Aridas, Sotiris B. Kotsiantis, Michael N. Vrahatis
2018	J	`jnl`	CST-Voting: A semi-supervised ensemble method for classification problems. J. Intell. Fuzzy Syst. Georgios Kostopoulos, Ioannis E. Livieris, Sotiris B. Kotsiantis, Vassilis Tampakas
2017	C	`conf`	Random Resampling in the One-Versus-All Strategy for Handling Multi-class Problems. EANN Christos K. Aridas, Stamatios-Aggelos N. Alexandropoulos, Sotiris B. Kotsiantis, Michael N. Vrahatis
2016	J	`jnl`	A Semisupervised Cascade Classification Algorithm. Appl. Comput. Intell. Soft Comput. Stamatis Karlos, Nikos Fazakis, Sotiris B. Kotsiantis, Kyriakos N. Sgarbas
2016	Misc	`conf`	Combining Prototype Selection with Local Boosting. AIAI Christos K. Aridas, Sotiris B. Kotsiantis, Michael N. Vrahatis
2016	Misc	`conf`	Increasing Diversity in Random Forests Using Naive Bayes. AIAI Christos K. Aridas, Sotiris B. Kotsiantis, Michael N. Vrahatis
2016	J	`jnl`	Self-Trained LMT for Semisupervised Learning. Comput. Intell. Neurosci. Nikos Fazakis, Stamatis Karlos, Sotiris B. Kotsiantis, Kyriakos N. Sgarbas
2016	—	`conf`	Speech Recognition Combining MFCCs and Image Features. SPECOM Stamatis Karlos, Nikos Fazakis, Katerina Karanikola, Sotiris B. Kotsiantis, Kyriakos N. Sgarbas
2015	—	`conf`	Combining random forest and support vector machines for semi-supervised learning. Panhellenic Conference on Informatics Christos K. Aridas, Sotiris B. Kotsiantis
2015	—	`conf`	Estimating student dropout in distance higher education using semi-supervised techniques. Panhellenic Conference on Informatics Georgios Kostopoulos, Sotiris B. Kotsiantis, Panagiotis E. Pintelas
2015	C	`conf`	Predicting Student Performance in Distance Higher Education Using Semi-supervised Techniques. MEDI Georgios Kostopoulos, Sotiris B. Kotsiantis, Panagiotis E. Pintelas
2015	C	`conf`	Self-Train LogitBoost for Semi-supervised Learning. EANN Stamatis Karlos, Nikos Fazakis, Sotiris B. Kotsiantis, Kyriakos N. Sgarbas
2015	—	`conf`	Speaker Identification Using Semi-supervised Learning. SPECOM Nikos Fazakis, Stamatis Karlos, Sotiris B. Kotsiantis, Kyriakos N. Sgarbas
2014	J	`jnl`	A hybrid decision tree classifier. J. Intell. Fuzzy Syst. Sotiris B. Kotsiantis
2014	J	`jnl`	Bagging and boosting variants for handling classifications problems: a survey. Knowl. Eng. Rev. Sotiris B. Kotsiantis
2014	J	`jnl`	Integrating global and local application of naive bayes classifier. Int. Arab J. Inf. Technol. Sotiris B. Kotsiantis
2014	J	`jnl`	Integrating global and local application of random subspace ensemble. J. Intell. Fuzzy Syst. Sotiris B. Kotsiantis
2013	J	`jnl`	Decision trees: a recent overview. Artif. Intell. Rev. Sotiris B. Kotsiantis
2012	—	`conf`	Credit Rating Using a Hybrid Voting Ensemble. SETN Elias Kamos, Foteini Matthaiou, Sotiris B. Kotsiantis
2012	—	`conf`	Forecasting Corporate Bankruptcy with an Ensemble of Classifiers. SETN Despina Deligianni, Sotiris B. Kotsiantis
2012	—	`conf`	Forecasting Fraudulent Financial Statements with Committee of Cost-Sensitive Decision Tree Classifiers. SETN Elias Zouboulidis, Sotiris B. Kotsiantis
2012	C	`conf`	Integrating Global and Local Application of Discriminative Multinomial Bayesian Classifier for Text Classification. ISI Emmanuel Pappas, Sotiris B. Kotsiantis
2012	J	`jnl`	Integrating Global and Local Voting of Classifiers. Cybern. Syst. Sotiris B. Kotsiantis
2012	J	`jnl`	Use of machine learning techniques for educational proposes: a decision support system for forecasting students' grades. Artif. Intell. Rev. Sotiris B. Kotsiantis
2011	J	`jnl`	A random subspace method that uses different instead of similar models for regression and classification problems. Int. J. Inf. Decis. Sci. Sotiris B. Kotsiantis
2011	J	`jnl`	An incremental ensemble of classifiers. Artif. Intell. Rev. Sotiris B. Kotsiantis
2011	J	`jnl`	Cascade Generalization with Reweighting Data for Handling Imbalanced Problems. Comput. J. Sotiris B. Kotsiantis
2011	J	`jnl`	Combining bagging, boosting, rotation forest and random subspace methods. Artif. Intell. Rev. Sotiris B. Kotsiantis
2011	J	`jnl`	Intelligent Systems and Knowledge Management (Part II). J. Comput. Methods Sci. Eng. Dimitris Kanellopoulos, Sotiris B. Kotsiantis, Panayiotis E. Pintelas
2010	J	`jnl`	A combinational incremental ensemble of classifiers as a technique for predicting students' performance in distance education. Knowl. Based Syst. Sotiris B. Kotsiantis, Kiriakos Patriarcheas, Michalis Nik Xenos
2010	J	`jnl`	Bagging different instead of similar models for regression and classification problems. Int. J. Comput. Appl. Technol. Sotiris B. Kotsiantis, Dimitris N. Kanellopoulos
2010	J	`jnl`	Cascade generalisation for ordinal problems. Int. J. Artif. Intell. Soft Comput. Sotiris B. Kotsiantis, Dimitris Kanellopoulos
2010	J	`jnl`	Financial Application of Multi-Instance Learning: Two Greek Case Studies. J. Convergence Inf. Technol. Sotiris B. Kotsiantis, Dimitris Kanellopoulos, Vasilis Tampakas
2010	J	`jnl`	Local rotation-based ensemble. Int. J. Knowl. Eng. Data Min. Sotiris B. Kotsiantis
2010	J	`jnl`	Rotation-based model trees for classification. Int. J. Data Anal. Tech. Strateg. Sotiris B. Kotsiantis
2009	J	`jnl`	Educational data mining: a case study for predicting dropout-prone students. Int. J. Knowl. Eng. Soft Data Paradigms Sotiris B. Kotsiantis
2009	J	`jnl`	Locally application of random subspace with simple Bayesian classifier. Int. J. Data Min. Model. Manag. Sotiris B. Kotsiantis
2009	J	`jnl`	Selective costing ensemble for handling imbalanced data sets. Int. J. Hybrid Intell. Syst. Sotiris B. Kotsiantis, Panayiotis E. Pintelas
2008	—	`conf`	Applying Machine Learning Techniques for Environmental Reporting. NCM (1) Sotiris B. Kotsiantis, Dimitris Kanellopoulos
2008	J	`jnl`	Handling imbalanced data sets with a modification of Decorate algorithm. Int. J. Comput. Appl. Technol. Sotiris B. Kotsiantis
2008	—	`conf`	Local Grading of Learners. Panhellenic Conference on Informatics Sotiris B. Kotsiantis
2008	J	`jnl`	Local reweight wrapper for the problem of imbalance. Int. J. Artif. Intell. Soft Comput. Sotiris B. Kotsiantis
2008	J	`jnl`	Locally application of cascade generalization for classification problems. Intell. Decis. Technol. Sotiris B. Kotsiantis
2008	—	`conf`	Stacking Cost Sensitive Models. Panhellenic Conference on Informatics Sotiris B. Kotsiantis
2007	Misc	`conf`	A Wrapper for Reweighting Training Instances for Handling Imbalanced Data Sets. AIAI M. Karagiannopoulos, D. Anyfantis, Sotiris B. Kotsiantis, Panayiotis E. Pintelas
2007	—	`conf`	Combining Bagging, Boosting and Dagging for Classification Problems. KES (2) Sotiris B. Kotsiantis, Dimitris Kanellopoulos
2007	J	`jnl`	Credit risk analysis using a hybrid data mining model. Int. J. Intell. Syst. Technol. Appl. Sotiris B. Kotsiantis
2007	Misc	`conf`	Robustness of learning techniques in handling class noise in imbalanced datasets. AIAI D. Anyfantis, M. Karagiannopoulos, Sotiris B. Kotsiantis, Panayiotis E. Pintelas
2007	J	`jnl`	Selective costing voting for bankruptcy prediction. Int. J. Knowl. Based Intell. Eng. Syst. Sotiris B. Kotsiantis, Dimitris Tzelepis, Euaggelos Koumanakos, Vasilis Tampakas
2007	J	`jnl`	Supervised Machine Learning: A Review of Classification Techniques. Informatica (Slovenia) Sotiris B. Kotsiantis
2007	—	`ch.`	Supervised Machine Learning: A Review of Classification Techniques. Emerging Artificial Intelligence Applications in Computer Engineering Sotiris B. Kotsiantis
2007	C	`conf`	Towards an ontology-based system for intelligent prediction of firms with fraudulent financial statements. ETFA Dimitris Kanellopoulos, Sotiris B. Kotsiantis, Vasilis Tampakas
2006	Misc	`conf`	Bagged Averaging of Regression Models. AIAI Sotiris B. Kotsiantis, Dimitris Kanellopoulos, Ioannis D. Zaharakis
2006	—	`conf`	Financial Application of Neural Networks: Two Case Studies in Greece. ICANN (2) Sotiris B. Kotsiantis, Euaggelos Koumanakos, Dimitris Tzelepis, Vasilis Tampakas
2006	—	`conf`	Local Additive Regression of Decision Stumps. SETN Sotiris B. Kotsiantis, Dimitris Kanellopoulos, Panayiotis E. Pintelas
2006	J	`jnl`	Local Boosting of Decision Stumps for Regression and Classification Problems. J. Comput. Sotiris B. Kotsiantis, Dimitris Kanellopoulos, Panayiotis E. Pintelas
2006	Misc	`conf`	Local Ordinal Classification. AIAI Sotiris B. Kotsiantis
2006	J	`jnl`	Local averaging of heterogeneous regression models. Int. J. Hybrid Intell. Syst. Sotiris B. Kotsiantis
2006	J	`jnl`	Machine learning: a review of classification and combining techniques. Artif. Intell. Rev. Sotiris B. Kotsiantis, Ioannis D. Zaharakis, Panayiotis E. Pintelas
2006	—	`conf`	Ontology-based Learning Applications: A Development Methodology. IASTED Conf. on Software Engineering Dimitris Kanellopoulos, Sotiris B. Kotsiantis, Panayiotis E. Pintelas
2006	—	`conf`	Predicting Fraudulent Financial Statements with Machine Learning Techniques. SETN Sotiris B. Kotsiantis, Euaggelos Koumanakos, Dimitris Tzelepis, Vasilis Tampakas
2005	C	`conf`	A Fuzzy Logic-Based Approach for Detecting Shifting Patterns in Cross-Cultural Data. IEA/AIE George E. Tsekouras, Dimitris Papageorgiou, Sotiris B. Kotsiantis, Christos Kalloniatis, Panayiotis E. Pintelas
2005	—	`conf`	Bagging Model Trees for Classification Problems. Panhellenic Conference on Informatics Sotiris B. Kotsiantis, George E. Tsekouras, Panayiotis E. Pintelas
2005	—	`conf`	Bagging Random Trees for Estimation of Tissue Softness. MLDM Sotiris B. Kotsiantis, George E. Tsekouras, Panayiotis E. Pintelas
2005	C	`conf`	Local Bagging of Decision Stumps. IEA/AIE Sotiris B. Kotsiantis, George E. Tsekouras, Panayiotis E. Pintelas
2005	J	`jnl`	Local voting of weak classifiers. Int. J. Knowl. Based Intell. Eng. Syst. Sotiris B. Kotsiantis, Panayiotis E. Pintelas
2005	J	`jnl`	Logitboost of Simple Bayesian Classifier. Informatica (Slovenia) Sotiris B. Kotsiantis, Panayiotis E. Pintelas
2005	—	`conf`	Modeling the Organoleptic Properties of Matured Wine Distillates. MLDM Sotiris B. Kotsiantis, George E. Tsekouras, C. Raptis, Panayiotis E. Pintelas
2005	B	`conf`	Predicting Students' Marks in Hellenic Open University. ICALT Sotiris B. Kotsiantis, Panayiotis E. Pintelas
2004	—	`conf`	A Cost Sensitive Technique for Ordinal Classification Problems. SETN Sotiris B. Kotsiantis, Panayiotis E. Pintelas
2004	—	`conf`	A Hybrid Decision Support Tool - Using Ensemble of Classifiers. ICEIS (2) Sotiris B. Kotsiantis, Panayiotis E. Pintelas
2004	J	`jnl`	A decision support prototype tool for predicting student performance in an ODL environment. Interact. Technol. Smart Educ. Sotiris B. Kotsiantis, Panayiotis E. Pintelas
2004	—	`conf`	An Online Ensemble of Classifiers. PRIS Sotiris B. Kotsiantis, Panayiotis E. Pintelas
2004	Misc	`conf`	Bagged Voting Ensembles. AIMSA Sotiris B. Kotsiantis, Panayiotis E. Pintelas
2004	—	`conf`	Fuzzy Clustering of Categorical Attributes and its Use in Analyzing Cultural Data. International Conference on Computational Intelligence George E. Tsekouras, Dimitris Papageorgiou, Sotiris B. Kotsiantis, Christos Kalloniatis, Panayiotis E. Pintelas
2004	Misc	`conf`	Increasing the Classification Accuracy of Simple Bayesian Classifier. AIMSA Sotiris B. Kotsiantis, Panayiotis E. Pintelas
2004	J	`jnl`	Predicting Students' Performance In Distance Learning Using Machine Learning Techniques. Appl. Artif. Intell. Sotiris B. Kotsiantis, Christos Pierrakeas, Panayiotis E. Pintelas
2003	B	`conf`	Preventing Student Dropout in Distance Learning Using Machine Learning Techniques. KES Sotiris B. Kotsiantis, Christos Pierrakeas, Panayiotis E. Pintelas