Sotiris B. Kotsiantis

Publication Activity (10 Years)

Years Active: 2003-2023
Publications (10 Years): 17

Top Topics

Top Venues

J. Intell. Fuzzy Syst.

Publications

Athanasios I. Salamanis, George A. Gravvanis, Sotiris B. Kotsiantis, Michael N. Vrahatis
Novel Sparse Feature Regression Method for Traffic Forecasting. Int. J. Artif. Intell. Tools 32 (1) (2023)
Stamatios-Aggelos N. Alexandropoulos, Christos K. Aridas, Sotiris B. Kotsiantis, George A. Gravvanis, Michael N. Vrahatis
Rotation forest of random subspace models. Intell. Decis. Technol. 16 (2) (2022)
Panos K. Syriopoulos, Sotiris B. Kotsiantis, Michael N. Vrahatis
Survey on KNN Methods in Data Science. LION (2022)
Vangjel Kazllarof, Sotiris B. Kotsiantis
Active Hidden Naive Bayes. PCI (2020)
Christos K. Aridas, Stamatis Karlos, Vasileios G. Kanas, Nikos Fazakis, Sotiris B. Kotsiantis
Uncertainty Based Under-Sampling for Learning Naive Bayes Classifiers Under Imbalanced Data Sets. IEEE Access 8 (2020)
Stamatios-Aggelos N. Alexandropoulos, Sotiris B. Kotsiantis, Michael N. Vrahatis
Data preprocessing in predictive data mining. Knowl. Eng. Rev. 34 (2019)
Stamatios-Aggelos N. Alexandropoulos, Christos K. Aridas, Sotiris B. Kotsiantis, Michael N. Vrahatis
Stacking Strong Ensembles of Classifiers. AIAI (2019)
Christos K. Aridas, Sotiris B. Kotsiantis, Michael N. Vrahatis
Hybrid local boosting utilizing unlabeled data in classification tasks. Evol. Syst. 10 (1) (2019)
Georgios S. Temponeras, Stamatios-Aggelos N. Alexandropoulos, Sotiris B. Kotsiantis, Michael N. Vrahatis
Financial Fraudulent Statements Detection through a Deep Dense Artificial Neural Network. IISA (2019)
Stamatios-Aggelos N. Alexandropoulos, Christos K. Aridas, Sotiris B. Kotsiantis, Michael N. Vrahatis
A Deep Dense Neural Network for Bankruptcy Prediction. EANN (2019)
Georgios Kostopoulos, Ioannis E. Livieris, Sotiris B. Kotsiantis, Vassilis Tampakas
CST-Voting: A semi-supervised ensemble method for classification problems. J. Intell. Fuzzy Syst. 35 (1) (2018)
Christos K. Aridas, Stamatios-Aggelos N. Alexandropoulos, Sotiris B. Kotsiantis, Michael N. Vrahatis
Random Resampling in the One-Versus-All Strategy for Handling Multi-class Problems. EANN (2017)
Stamatis Karlos, Nikos Fazakis, Katerina Karanikola, Sotiris B. Kotsiantis, Kyriakos N. Sgarbas
Speech Recognition Combining MFCCs and Image Features. SPECOM (2016)
Christos K. Aridas, Sotiris B. Kotsiantis, Michael N. Vrahatis
Combining Prototype Selection with Local Boosting. AIAI (2016)
Nikos Fazakis, Stamatis Karlos, Sotiris B. Kotsiantis, Kyriakos N. Sgarbas
Self-Trained LMT for Semisupervised Learning. Comput. Intell. Neurosci. 2016 (2016)
Stamatis Karlos, Nikos Fazakis, Sotiris B. Kotsiantis, Kyriakos N. Sgarbas
A Semisupervised Cascade Classification Algorithm. Appl. Comput. Intell. Soft Comput. 2016 (2016)
Christos K. Aridas, Sotiris B. Kotsiantis, Michael N. Vrahatis
Increasing Diversity in Random Forests Using Naive Bayes. AIAI (2016)
Georgios Kostopoulos, Sotiris B. Kotsiantis, Panagiotis E. Pintelas
Estimating student dropout in distance higher education using semi-supervised techniques. Panhellenic Conference on Informatics (2015)
Stamatis Karlos, Nikos Fazakis, Sotiris B. Kotsiantis, Kyriakos N. Sgarbas
Self-Train LogitBoost for Semi-supervised Learning. EANN (2015)
Christos K. Aridas, Sotiris B. Kotsiantis
Combining random forest and support vector machines for semi-supervised learning. Panhellenic Conference on Informatics (2015)
Nikos Fazakis, Stamatis Karlos, Sotiris B. Kotsiantis, Kyriakos N. Sgarbas
Speaker Identification Using Semi-supervised Learning. SPECOM (2015)
Georgios Kostopoulos, Sotiris B. Kotsiantis, Panagiotis E. Pintelas
Predicting Student Performance in Distance Higher Education Using Semi-supervised Techniques. MEDI (2015)
Sotiris B. Kotsiantis
A hybrid decision tree classifier. J. Intell. Fuzzy Syst. 26 (1) (2014)
Sotiris B. Kotsiantis
Bagging and boosting variants for handling classifications problems: a survey. Knowl. Eng. Rev. 29 (1) (2014)
Sotiris B. Kotsiantis
Integrating global and local application of random subspace ensemble. J. Intell. Fuzzy Syst. 26 (2) (2014)
Sotiris B. Kotsiantis
Integrating global and local application of naive bayes classifier. Int. Arab J. Inf. Technol. 11 (3) (2014)
Sotiris B. Kotsiantis
Decision trees: a recent overview. Artif. Intell. Rev. 39 (4) (2013)
Elias Zouboulidis, Sotiris B. Kotsiantis
Forecasting Fraudulent Financial Statements with Committee of Cost-Sensitive Decision Tree Classifiers. SETN (2012)
Despina Deligianni, Sotiris B. Kotsiantis
Forecasting Corporate Bankruptcy with an Ensemble of Classifiers. SETN (2012)
Emmanuel Pappas, Sotiris B. Kotsiantis
Integrating Global and Local Application of Discriminative Multinomial Bayesian Classifier for Text Classification. ISI (2012)
Elias Kamos, Foteini Matthaiou, Sotiris B. Kotsiantis
Credit Rating Using a Hybrid Voting Ensemble. SETN (2012)
Sotiris B. Kotsiantis
Use of machine learning techniques for educational proposes: a decision support system for forecasting students' grades. Artif. Intell. Rev. 37 (4) (2012)
Sotiris B. Kotsiantis
Integrating Global and Local Voting of Classifiers. Cybern. Syst. 43 (5) (2012)
Sotiris B. Kotsiantis
Cascade Generalization with Reweighting Data for Handling Imbalanced Problems. Comput. J. 54 (9) (2011)
Sotiris B. Kotsiantis
An incremental ensemble of classifiers. Artif. Intell. Rev. 36 (4) (2011)
Sotiris B. Kotsiantis
A random subspace method that uses different instead of similar models for regression and classification problems. Int. J. Inf. Decis. Sci. 3 (2) (2011)
Sotiris B. Kotsiantis
Combining bagging, boosting, rotation forest and random subspace methods. Artif. Intell. Rev. 35 (3) (2011)
Dimitris Kanellopoulos, Sotiris B. Kotsiantis, Panayiotis E. Pintelas
Intelligent Systems and Knowledge Management (Part II). J. Comput. Methods Sci. Eng. 11 (3) (2011)
Sotiris B. Kotsiantis
Rotation-based model trees for classification. Int. J. Data Anal. Tech. Strateg. 2 (1) (2010)
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) (2010)
Sotiris B. Kotsiantis, Dimitris Kanellopoulos, Vasilis Tampakas
Financial Application of Multi-Instance Learning: Two Greek Case Studies. J. Convergence Inf. Technol. 5 (8) (2010)
Sotiris B. Kotsiantis, Dimitris N. Kanellopoulos
Bagging different instead of similar models for regression and classification problems. Int. J. Comput. Appl. Technol. 37 (1) (2010)
Sotiris B. Kotsiantis
Local rotation-based ensemble. Int. J. Knowl. Eng. Data Min. 1 (2) (2010)
Sotiris B. Kotsiantis, Dimitris Kanellopoulos
Cascade generalisation for ordinal problems. Int. J. Artif. Intell. Soft Comput. 2 (1/2) (2010)
Sotiris B. Kotsiantis, Panayiotis E. Pintelas
Selective costing ensemble for handling imbalanced data sets. Int. J. Hybrid Intell. Syst. 6 (3) (2009)
Sotiris B. Kotsiantis
Educational data mining: a case study for predicting dropout-prone students. Int. J. Knowl. Eng. Soft Data Paradigms 1 (2) (2009)
Sotiris B. Kotsiantis
Locally application of random subspace with simple Bayesian classifier. Int. J. Data Min. Model. Manag. 1 (4) (2009)
Sotiris B. Kotsiantis
Local reweight wrapper for the problem of imbalance. Int. J. Artif. Intell. Soft Comput. 1 (1) (2008)
Sotiris B. Kotsiantis, Dimitris Kanellopoulos
Applying Machine Learning Techniques for Environmental Reporting. NCM (1) (2008)
Sotiris B. Kotsiantis
Local Grading of Learners. Panhellenic Conference on Informatics (2008)
Sotiris B. Kotsiantis
Stacking Cost Sensitive Models. Panhellenic Conference on Informatics (2008)
Sotiris B. Kotsiantis
Handling imbalanced data sets with a modification of Decorate algorithm. Int. J. Comput. Appl. Technol. 33 (2/3) (2008)
Sotiris B. Kotsiantis
Locally application of cascade generalization for classification problems. Intell. Decis. Technol. 2 (4) (2008)
M. Karagiannopoulos, D. Anyfantis, Sotiris B. Kotsiantis, Panayiotis E. Pintelas
A Wrapper for Reweighting Training Instances for Handling Imbalanced Data Sets. AIAI (2007)
D. Anyfantis, M. Karagiannopoulos, Sotiris B. Kotsiantis, Panayiotis E. Pintelas
Robustness of learning techniques in handling class noise in imbalanced datasets. AIAI (2007)
Sotiris B. Kotsiantis, Dimitris Tzelepis, Euaggelos Koumanakos, Vasilis Tampakas
Selective costing voting for bankruptcy prediction. Int. J. Knowl. Based Intell. Eng. Syst. 11 (2) (2007)
Sotiris B. Kotsiantis
Supervised Machine Learning: A Review of Classification Techniques. Informatica (Slovenia) 31 (3) (2007)
Sotiris B. Kotsiantis, Dimitris Kanellopoulos
Combining Bagging, Boosting and Dagging for Classification Problems. KES (2) (2007)
Dimitris Kanellopoulos, Sotiris B. Kotsiantis, Vasilis Tampakas
Towards an ontology-based system for intelligent prediction of firms with fraudulent financial statements. ETFA (2007)
Sotiris B. Kotsiantis
Credit risk analysis using a hybrid data mining model. Int. J. Intell. Syst. Technol. Appl. 2 (4) (2007)
Sotiris B. Kotsiantis, Ioannis D. Zaharakis, Panayiotis E. Pintelas
Machine learning: a review of classification and combining techniques. Artif. Intell. Rev. 26 (3) (2006)
Sotiris B. Kotsiantis
Local Ordinal Classification. AIAI (2006)
Sotiris B. Kotsiantis, Dimitris Kanellopoulos, Ioannis D. Zaharakis
Bagged Averaging of Regression Models. AIAI (2006)
Sotiris B. Kotsiantis, Dimitris Kanellopoulos, Panayiotis E. Pintelas
Local Boosting of Decision Stumps for Regression and Classification Problems. J. Comput. 1 (4) (2006)
Sotiris B. Kotsiantis, Euaggelos Koumanakos, Dimitris Tzelepis, Vasilis Tampakas
Financial Application of Neural Networks: Two Case Studies in Greece. ICANN (2) (2006)
Sotiris B. Kotsiantis
Local averaging of heterogeneous regression models. Int. J. Hybrid Intell. Syst. 3 (2) (2006)
Sotiris B. Kotsiantis, Euaggelos Koumanakos, Dimitris Tzelepis, Vasilis Tampakas
Predicting Fraudulent Financial Statements with Machine Learning Techniques. SETN (2006)
Sotiris B. Kotsiantis, Dimitris Kanellopoulos, Panayiotis E. Pintelas
Local Additive Regression of Decision Stumps. SETN (2006)
Dimitris Kanellopoulos, Sotiris B. Kotsiantis, Panayiotis E. Pintelas
Ontology-based Learning Applications: A Development Methodology. IASTED Conf. on Software Engineering (2006)
Sotiris B. Kotsiantis, George E. Tsekouras, Panayiotis E. Pintelas
Local Bagging of Decision Stumps. IEA/AIE (2005)
Sotiris B. Kotsiantis, Panayiotis E. Pintelas
Predicting Students' Marks in Hellenic Open University. ICALT (2005)
Sotiris B. Kotsiantis, George E. Tsekouras, C. Raptis, Panayiotis E. Pintelas
Modeling the Organoleptic Properties of Matured Wine Distillates. MLDM (2005)
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)
Sotiris B. Kotsiantis, George E. Tsekouras, Panayiotis E. Pintelas
Bagging Random Trees for Estimation of Tissue Softness. MLDM (2005)
Sotiris B. Kotsiantis, George E. Tsekouras, Panayiotis E. Pintelas
Bagging Model Trees for Classification Problems. Panhellenic Conference on Informatics (2005)
Sotiris B. Kotsiantis, Panayiotis E. Pintelas
Logitboost of Simple Bayesian Classifier. Informatica (Slovenia) 29 (1) (2005)
Sotiris B. Kotsiantis, Panayiotis E. Pintelas
Local voting of weak classifiers. Int. J. Knowl. Based Intell. Eng. Syst. 9 (3) (2005)
Sotiris B. Kotsiantis, Panayiotis E. Pintelas
A decision support prototype tool for predicting student performance in an ODL environment. Interact. Technol. Smart Educ. 1 (4) (2004)
Sotiris B. Kotsiantis, Panayiotis E. Pintelas
An Online Ensemble of Classifiers. PRIS (2004)
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)
Sotiris B. Kotsiantis, Panayiotis E. Pintelas
A Cost Sensitive Technique for Ordinal Classification Problems. SETN (2004)
Sotiris B. Kotsiantis, Panayiotis E. Pintelas
A Hybrid Decision Support Tool - Using Ensemble of Classifiers. ICEIS (2) (2004)
Sotiris B. Kotsiantis, Panayiotis E. Pintelas
Increasing the Classification Accuracy of Simple Bayesian Classifier. AIMSA (2004)
Sotiris B. Kotsiantis, Christos Pierrakeas, Panayiotis E. Pintelas
Predicting Students' Performance In Distance Learning Using Machine Learning Techniques. Appl. Artif. Intell. 18 (5) (2004)
Sotiris B. Kotsiantis, Panayiotis E. Pintelas
Bagged Voting Ensembles. AIMSA (2004)
Sotiris B. Kotsiantis, Christos Pierrakeas, Panayiotis E. Pintelas
Preventing Student Dropout in Distance Learning Using Machine Learning Techniques. KES (2003)