Sotiris B. Kotsiantis

According to our database1, Sotiris B. Kotsiantis authored at least 132 papers between 2003 and 2020.

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Bibliography

2020
The Variability of the Reasons for Student Dropout in Distance Learning and the Prediction of Dropout-Prone Students.
Proceedings of the Machine Learning Paradigms - Advances in Learning Analytics, 2020

Explainable Machine Learning Framework for Image Classification Problems: Case Study on Glioma Cancer Prediction.
J. Imaging, 2020

Polarity, emotions and online activity of students and tutors as features in predicting grades.
Intell. Decis. Technol., 2020

An active learning ensemble method for regression tasks.
Intell. Data Anal., 2020

Special issue on "Intelligent and fuzzy systems in data science and big data".
Evol. Intell., 2020

University students' intention to use search engines for research purposes: A structural equation modeling approach.
Educ. Inf. Technol., 2020

A Soft-Voting Ensemble Based Co-Training Scheme Using Static Selection for Binary Classification Problems.
Algorithms, 2020

Iterative Robust Semi-Supervised Missing Data Imputation.
IEEE Access, 2020

Uncertainty Based Under-Sampling for Learning Naive Bayes Classifiers Under Imbalanced Data Sets.
IEEE Access, 2020

2019
Multiview Learning for Early Prognosis of Academic Performance: A Case Study.
IEEE Trans. Learn. Technol., 2019

A multi-scheme semi-supervised regression approach.
Pattern Recognit. Lett., 2019

Data preprocessing in predictive data mining.
Knowl. Eng. Rev., 2019

A Semi-Supervised Regression Algorithm for Grade Prediction of Students in Distance Learning Courses.
Int. J. Artif. Intell. Tools, 2019

Hybrid local boosting utilizing unlabeled data in classification tasks.
Evol. Syst., 2019

Combination of Active Learning and Semi-Supervised Learning under a Self-Training Scheme.
Entropy, 2019

Active learning Rotation Forest for multiclass classification.
Comput. Intell., 2019

A hybrid method for missing value imputation.
Proceedings of the 23rd Pan-Hellenic Conference on Informatics, 2019

Performance Evaluation and Comparison of Multi-objective optimization Algorithms.
Proceedings of the 10th International Conference on Information, 2019

Financial Fraudulent Statements Detection through a Deep Dense Artificial Neural Network.
Proceedings of the 10th International Conference on Information, 2019

Multi-objective Optimization of C4.5 Decision Tree for Predicting Student Academic Performance.
Proceedings of the 10th International Conference on Information, 2019

Combining Active Learning with Self-train algorithm for classification of multimodal problems.
Proceedings of the 10th International Conference on Information, 2019

Self-trained eXtreme Gradient Boosting Trees.
Proceedings of the 10th International Conference on Information, 2019

Investigating the Benefits of Exploiting Incremental Learners Under Active Learning Scheme.
Proceedings of the Artificial Intelligence Applications and Innovations, 2019

Stacking Strong Ensembles of Classifiers.
Proceedings of the Artificial Intelligence Applications and Innovations, 2019

A Deep Dense Neural Network for Bankruptcy Prediction.
Proceedings of the Engineering Applications of Neural Networks, 2019

2018
CST-Voting: A semi-supervised ensemble method for classification problems.
J. Intell. Fuzzy Syst., 2018

Semi-supervised regression: A recent review.
J. Intell. Fuzzy Syst., 2018

Forecasting students' success in an open university.
Int. J. Learn. Technol., 2018

Optimized Active Learning Strategy for Audiovisual Speaker Recognition.
Proceedings of the Speech and Computer - 20th International Conference, 2018

Local weighted Averaged 2-Dependence Estimator.
Proceedings of the 10th Hellenic Conference on Artificial Intelligence, 2018

A Semi-supervised regressor based on model trees.
Proceedings of the 10th Hellenic Conference on Artificial Intelligence, 2018

An incrementally updateable ensemble learner.
Proceedings of the 22nd Pan-Hellenic Conference on Informatics, 2018

An effective LA approach to predict student achievement.
Proceedings of the 22nd Pan-Hellenic Conference on Informatics, 2018

Predicting University Students' Grades Based on Previous Academic Achievements.
Proceedings of the 9th International Conference on Information, 2018

Measuring Engagement to Assess Performance of Students in Distance Learning.
Proceedings of the 9th International Conference on Information, 2018

An incremental self-trained ensemble algorithm.
Proceedings of the 2018 IEEE Conference on Evolving and Adaptive Intelligent Systems, 2018

Active fuzzy rule induction.
Proceedings of the 2018 IEEE Conference on Evolving and Adaptive Intelligent Systems, 2018

2017
Self-trained Rotation Forest for semi-supervised learning.
J. Intell. Fuzzy Syst., 2017

Students' evaluation of tutors in distance education: a quasi-longitudinal study.
Int. J. Learn. Technol., 2017

Self-Trained Stacking Model for Semi-Supervised Learning.
Int. J. Artif. Intell. Tools, 2017

Locally application of naive Bayes for self-training.
Evol. Syst., 2017

Automated hand gesture recognition exploiting Active Learning methods.
Proceedings of the 21st Pan-Hellenic Conference on Informatics, 2017

Enhancing high school students' performance based on semi-supervised methods.
Proceedings of the 8th International Conference on Information, 2017

Early dropout prediction in distance higher education using active learning.
Proceedings of the 8th International Conference on Information, 2017

Predicting Student Performance in Distance Higher Education Using Active Learning.
Proceedings of the Engineering Applications of Neural Networks, 2017

Using Active Learning Methods for Predicting Fraudulent Financial Statements.
Proceedings of the Engineering Applications of Neural Networks, 2017

Random Resampling in the One-Versus-All Strategy for Handling Multi-class Problems.
Proceedings of the Engineering Applications of Neural Networks, 2017

A Prognosis of Junior High School Students' Performance Based on Active Learning Methods.
Proceedings of the Brain Function Assessment in Learning - First International Conference, 2017

Evaluating Active Learning Methods for Bankruptcy Prediction.
Proceedings of the Brain Function Assessment in Learning - First International Conference, 2017

2016
Self-Trained LMT for Semisupervised Learning.
Comput. Intell. Neurosci., 2016

A Semisupervised Cascade Classification Algorithm.
Appl. Comput. Intell. Soft Comput., 2016

Speech Recognition Combining MFCCs and Image Features.
Proceedings of the Speech and Computer - 18th International Conference, 2016

Automated hand gesture recognition for educational applications.
Proceedings of the 20th Pan-Hellenic Conference on Informatics, 2016

Semi-supervised forecasting of fraudulent financial statements.
Proceedings of the 20th Pan-Hellenic Conference on Informatics, 2016

Effectiveness of semi-supervised learning in bankruptcy prediction.
Proceedings of the 7th International Conference on Information, 2016

Self-labeled Hidden Naive Bayes algorithm for semi-supervised classification.
Proceedings of the 7th International Conference on Information, 2016

Combining Prototype Selection with Local Boosting.
Proceedings of the Artificial Intelligence Applications and Innovations, 2016

Increasing Diversity in Random Forests Using Naive Bayes.
Proceedings of the Artificial Intelligence Applications and Innovations, 2016

2015
Speaker Identification Using Semi-supervised Learning.
Proceedings of the Speech and Computer - 17th International Conference, 2015

Estimating student dropout in distance higher education using semi-supervised techniques.
Proceedings of the 19th Panhellenic Conference on Informatics, 2015

Combining random forest and support vector machines for semi-supervised learning.
Proceedings of the 19th Panhellenic Conference on Informatics, 2015

Predicting Student Performance in Distance Higher Education Using Semi-supervised Techniques.
Proceedings of the Model and Data Engineering - 5th International Conference, 2015

Combining ensembles algorithms of symbolic learners.
Proceedings of the 6th International Conference on Information, 2015

Integrating global and local boosting.
Proceedings of the 6th International Conference on Information, 2015

Self-Train LogitBoost for Semi-supervised Learning.
Proceedings of the Engineering Applications of Neural Networks, 2015

2014
Bagging and boosting variants for handling classifications problems: a survey.
Knowl. Eng. Rev., 2014

Integrating global and local application of random subspace ensemble.
J. Intell. Fuzzy Syst., 2014

A hybrid decision tree classifier.
J. Intell. Fuzzy Syst., 2014

Integrating global and local application of naive bayes classifier.
Int. Arab J. Inf. Technol., 2014

A hybrid Machine Learning methodology for imbalanced datasets.
Proceedings of the 5th International Conference on Information, 2014

2013
Decision trees: a recent overview.
Artif. Intell. Rev., 2013

2012
Evaluating and recommending Greek newspapers' websites using clustering.
Program, 2012

Integrating Global and Local Voting of Classifiers.
Cybern. Syst., 2012

Use of machine learning techniques for educational proposes: a decision support system for forecasting students' grades.
Artif. Intell. Rev., 2012

Forecasting Fraudulent Financial Statements with Committee of Cost-Sensitive Decision Tree Classifiers.
Proceedings of the Artificial Intelligence: Theories and Applications, 2012

Credit Rating Using a Hybrid Voting Ensemble.
Proceedings of the Artificial Intelligence: Theories and Applications, 2012

Forecasting Corporate Bankruptcy with an Ensemble of Classifiers.
Proceedings of the Artificial Intelligence: Theories and Applications, 2012

Integrating Global and Local Application of Discriminative Multinomial Bayesian Classifier for Text Classification.
Proceedings of the Intelligent Informatics, 2012

2011
Intelligent Systems and Knowledge Management (Part II).
J. Comput. Methods Sci. Eng., 2011

A random subspace method that uses different instead of similar models for regression and classification problems.
Int. J. Inf. Decis. Sci., 2011

Cascade Generalization with Reweighting Data for Handling Imbalanced Problems.
Comput. J., 2011

An incremental ensemble of classifiers.
Artif. Intell. Rev., 2011

Combining bagging, boosting, rotation forest and random subspace methods.
Artif. Intell. Rev., 2011

2010
A combinational incremental ensemble of classifiers as a technique for predicting students' performance in distance education.
Knowl. Based Syst., 2010

Financial Application of Multi-Instance Learning: Two Greek Case Studies.
J. Convergence Inf. Technol., 2010

Local rotation-based ensemble.
Int. J. Knowl. Eng. Data Min., 2010

Rotation-based model trees for classification.
Int. J. Data Anal. Tech. Strateg., 2010

Bagging different instead of similar models for regression and classification problems.
Int. J. Comput. Appl. Technol., 2010

Cascade generalisation for ordinal problems.
Int. J. Artif. Intell. Soft Comput., 2010

2009
Educational data mining: a case study for predicting dropout-prone students.
Int. J. Knowl. Eng. Soft Data Paradigms, 2009

Selective costing ensemble for handling imbalanced data sets.
Int. J. Hybrid Intell. Syst., 2009

Locally application of random subspace with simple Bayesian classifier.
Int. J. Data Min. Model. Manag., 2009

2008
Handling imbalanced data sets with a modification of Decorate algorithm.
Int. J. Comput. Appl. Technol., 2008

Local reweight wrapper for the problem of imbalance.
Int. J. Artif. Intell. Soft Comput., 2008

Locally application of cascade generalization for classification problems.
Intell. Decis. Technol., 2008

Stacking Cost Sensitive Models.
Proceedings of the Panhellenic Conference on Informatics, 2008

Local Grading of Learners.
Proceedings of the Panhellenic Conference on Informatics, 2008

Applying Machine Learning Techniques for Environmental Reporting.
Proceedings of the NCM 2008, The Fourth International Conference on Networked Computing and Advanced Information Management, Gyeongju, Korea, September 2-4, 2008, 2008

2007
Supervised Machine Learning: A Review of Classification Techniques.
Proceedings of the Emerging Artificial Intelligence Applications in Computer Engineering, 2007

Selective costing voting for bankruptcy prediction.
Int. J. Knowl. Based Intell. Eng. Syst., 2007

Supervised Machine Learning: A Review of Classification Techniques.
Informatica (Slovenia), 2007

Credit risk analysis using a hybrid data mining model.
Int. J. Intell. Syst. Technol. Appl., 2007

Combining Bagging, Boosting and Dagging for Classification Problems.
Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2007

A Wrapper for Reweighting Training Instances for Handling Imbalanced Data Sets.
Proceedings of the Artificial Intelligence and Innovations 2007: from Theory to Applications, 2007

Robustness of learning techniques in handling class noise in imbalanced datasets.
Proceedings of the Artificial Intelligence and Innovations 2007: from Theory to Applications, 2007

Towards an ontology-based system for intelligent prediction of firms with fraudulent financial statements.
Proceedings of 12th IEEE International Conference on Emerging Technologies and Factory Automation, 2007

2006
Local Boosting of Decision Stumps for Regression and Classification Problems.
J. Comput., 2006

Local averaging of heterogeneous regression models.
Int. J. Hybrid Intell. Syst., 2006

Machine learning: a review of classification and combining techniques.
Artif. Intell. Rev., 2006

Predicting Fraudulent Financial Statements with Machine Learning Techniques.
Proceedings of the Advances in Artificial Intelligence, 4th Helenic Conference on AI, 2006

Local Additive Regression of Decision Stumps.
Proceedings of the Advances in Artificial Intelligence, 4th Helenic Conference on AI, 2006

Bagged Averaging of Regression Models.
Proceedings of the Artificial Intelligence Applications and Innovations, 2006

Local Ordinal Classification.
Proceedings of the Artificial Intelligence Applications and Innovations, 2006

Financial Application of Neural Networks: Two Case Studies in Greece.
Proceedings of the Artificial Neural Networks, 2006

Ontology-based Learning Applications: A Development Methodology.
Proceedings of the IASTED International Conference on Software Engineering, 2006

2005
Local voting of weak classifiers.
Int. J. Knowl. Based Intell. Eng. Syst., 2005

Logitboost of Simple Bayesian Classifier.
Informatica (Slovenia), 2005

Bagging Model Trees for Classification Problems.
Proceedings of the Advances in Informatics, 2005

Modeling the Organoleptic Properties of Matured Wine Distillates.
Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2005

Bagging Random Trees for Estimation of Tissue Softness.
Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2005

A Fuzzy Logic-Based Approach for Detecting Shifting Patterns in Cross-Cultural Data.
Proceedings of the Innovations in Applied Artificial Intelligence, 2005

Local Bagging of Decision Stumps.
Proceedings of the Innovations in Applied Artificial Intelligence, 2005

Predicting Students' Marks in Hellenic Open University.
Proceedings of the 5th IEEE International Conference on Advanced Learning Technologies, 2005

2004
A decision support prototype tool for predicting student performance in an ODL environment.
Interact. Technol. Smart Educ., 2004

Predicting Students' Performance In Distance Learning Using Machine Learning Techniques.
Appl. Artif. Intell., 2004

A Cost Sensitive Technique for Ordinal Classification Problems.
Proceedings of the Methods and Applications of Artificial Intelligence, 2004

An Online Ensemble of Classifiers.
Proceedings of the Pattern Recognition in Information Systems, 2004

Fuzzy Clustering of Categorical Attributes and its Use in Analyzing Cultural Data.
Proceedings of the International Conference on Computational Intelligence, 2004

A Hybrid Decision Support Tool - Using Ensemble of Classifiers.
Proceedings of the ICEIS 2004, 2004

Increasing the Classification Accuracy of Simple Bayesian Classifier.
Proceedings of the Artificial Intelligence: Methodology, 2004

Bagged Voting Ensembles.
Proceedings of the Artificial Intelligence: Methodology, 2004

2003
Preventing Student Dropout in Distance Learning Using Machine Learning Techniques.
Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2003


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