Sotiris B. Kotsiantis

According to our database, Sotiris B. Kotsiantis authored at least 172 papers between 2003 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

Temporal Dynamics of Citizen-Reported Urban Challenges: A Comprehensive Time Series Analysis.

Andreas F. Gkontzis, Sotiris Kotsiantis, Georgios Feretzakis, Vassilios S. Verykios

Big Data Cogn. Comput., March, 2024

Enhancing Urban Resilience: Smart City Data Analyses, Forecasts, and Digital Twin Techniques at the Neighborhood Level.

Andreas F. Gkontzis, Sotiris Kotsiantis, Georgios Feretzakis, Vassilios S. Verykios

Future Internet, February, 2024

2023

A generic sparse regression imputation method for time series and tabular data.

Athanasios I. Salamanis, George A. Gravvanis, Sotiris Kotsiantis, Konstantinos M. Giannoutakis

Knowl. Based Syst., November, 2023

A multivariate ensemble learning method for medium-term energy forecasting.

Charalampos M. Liapis, Aikaterini Karanikola, Sotiris Kotsiantis

Neural Comput. Appl., October, 2023

A multi-view-CNN framework for deep representation learning in image classification.

Emmanuel Pintelas, Ioannis E. Livieris, Sotiris Kotsiantis, Panayiotis E. Pintelas

Comput. Vis. Image Underst., July, 2023

Special Issue on Machine Learning and AI for Sensors.

Panagiotis E. Pintelas, Sotiris Kotsiantis, Ioannis E. Livieris

Sensors, March, 2023

Novel Sparse Feature Regression Method for Traffic Forecasting.

Athanasios I. Salamanis, George A. Gravvanis, Sotiris B. Kotsiantis, Michael N. Vrahatis

Int. J. Artif. Intell. Tools, February, 2023

Investigating Deep Stock Market Forecasting with Sentiment Analysis.

Charalampos M. Liapis, Aikaterini Karanikola, Sotiris Kotsiantis

Entropy, February, 2023

Classification of acoustical signals by combining active learning strategies with semi-supervised learning schemes.

Stamatis Karlos, Christos K. Aridas, Vasileios G. Kanas, Sotiris Kotsiantis

Neural Comput. Appl., 2023

Temporal Convolutional Networks and BERT-Based Multi-Label Emotion Analysis for Financial Forecasting.

Charalampos M. Liapis, Sotiris Kotsiantis

Inf., 2023

Financial sentiment analysis: Classic methods vs. deep learning models.

Aikaterini Karanikola, Gregory Davrazos, Charalampos M. Liapis, Sotiris Kotsiantis

Intell. Decis. Technol., 2023

IoT-Enabled Crop Recommendation in Smart Agriculture Using Machine Learning.

Gregory Davrazos, Theodor Panagiotakopoulos, Sotiris Kotsiantis, Achilles Kameas

Proceedings of the 14th International Conference on Information, 2023

IoT Device Identification Using a Meta-Ensemble Multi-Class Classifier.

Gregory Davrazos, Theodor Panagiotakopoulos, Sotiris Kotsiantis, Achilles Kameas

Proceedings of the 14th International Conference on Information, 2023

Android Malware Detection in IoT Mobile Devices using a Meta-ensemble Classifier.

Gregory Davrazos, Theodor Panagiotakopoulos, Sotiris Kotsiantis, Achilles Kameas

Proceedings of the 14th International Conference on Information, 2023

Predicting Cost of Municipal Waste Management using IoT Data and Machine Learning.

Gregory Davrazos, Theodor Panagiotakopoulos, Sotiris Kotsiantis, Achilles Kameas

Proceedings of the 14th International Conference on Information, 2023

Active Learning Query Strategy Selection Using Dataset Meta-features Extraction.

Vangjel Kazllarof, Sotiris Kotsiantis

Proceedings of the Artificial Intelligence Applications and Innovations, 2023

Water Quality Estimation from IoT Sensors Using a Meta-ensemble.

Gregory Davrazos, Theodor Panagiotakopoulos, Sotiris Kotsiantis

Proceedings of the Artificial Intelligence Applications and Innovations. AIAI 2023 IFIP WG 12.5 International Workshops, 2023

2022

Meteorological Data Warehousing and Analysis for Supporting Air Navigation.

Georgia Garani, Dionysios Papadatos, Sotiris Kotsiantis, Vassilios S. Verykios

Informatics, December, 2022

A predictive analytics framework as a countermeasure for attrition of students.

Andreas F. Gkontzis, Sotiris Kotsiantis, Christos T. Panagiotakopoulos, Vassilios S. Verykios

Interact. Learn. Environ., 2022

Rotation forest of random subspace models.

Stamatios-Aggelos N. Alexandropoulos, Christos K. Aridas, Sotiris B. Kotsiantis, George A. Gravvanis, Michael N. Vrahatis

Intell. Decis. Technol., 2022

Supervised machine learning models for student performance prediction.

Nikolaos S. Alachiotis, Sotiris Kotsiantis, Evangelos Sakkopoulos, Vassilios S. Verykios

Intell. Decis. Technol., 2022

Energy Balance Forecasting: An Extensive Multivariate Regression Models Comparison.

Charalampos M. Liapis, Sotiris Kotsiantis

Proceedings of the SETN 2022: 12th Hellenic Conference on Artificial Intelligence, Corfu, Greece, September 7, 2022

Human Activity Recognition using Time Series Feature Extraction and Active Learning.

Vangjel Kazllarof, Sotiris Kotsiantis

Proceedings of the SETN 2022: 12th Hellenic Conference on Artificial Intelligence, Corfu, Greece, September 7, 2022

Survey on KNN Methods in Data Science.

Panos K. Syriopoulos, Sotiris B. Kotsiantis, Michael N. Vrahatis

Proceedings of the Learning and Intelligent Optimization - 16th International Conference, 2022

Energy Load Forecasting: Investigating Mid-Term Predictions with Ensemble Learners.

Charalampos M. Liapis, Aikaterini Karanikola, Sotiris Kotsiantis

Proceedings of the Artificial Intelligence Applications and Innovations, 2022

2021

Editorial: Applications of Fuzzy Systems in Data Science and Big Data.

Gautam Srivastava, Jerry Chun-Wei Lin, Dragan Pamucar, Sotiris Kotsiantis

IEEE Trans. Fuzzy Syst., 2021

A novel explainable image classification framework: case study on skin cancer and plant disease prediction.

Emmanuel Pintelas, Meletis Liaskos, Ioannis E. Livieris, Sotiris Kotsiantis, Panagiotis E. Pintelas

Neural Comput. Appl., 2021

Fuzzy-based active learning for predicting student academic performance using autoML: a step-wise approach.

Maria Tsiakmaki, Georgios Kostopoulos, Sotiris Kotsiantis, Omiros Ragos

J. Comput. High. Educ., 2021

Investigating cluster validation metrics for optimal number of clusters determination.

Aikaterini Karanikola, Charalampos M. Liapis, Sotiris Kotsiantis

Intell. Decis. Technol., 2021

An adaptive cluster-based sparse autoregressive model for large-scale multi-step traffic forecasting.

Athanasios I. Salamanis, Anastasia-Dimitra Lipitakis, George A. Gravvanis, Sotiris Kotsiantis, Dimosthenis Anagnostopoulos

Expert Syst. Appl., 2021

Explainable AI: A Review of Machine Learning Interpretability Methods.

Pantelis Linardatos, Vasilis Papastefanopoulos, Sotiris Kotsiantis

Entropy, 2021

A Multi-Method Survey on the Use of Sentiment Analysis in Multivariate Financial Time Series Forecasting.

Charalampos M. Liapis, Aikaterini Karanikola, Sotiris Kotsiantis

Entropy, 2021

Interpretable Models for Early Prediction of Certification in MOOCs: A Case Study on a MOOC for Smart City Professionals.

Georgios Kostopoulos, Theodor Panagiotakopoulos, Sotiris Kotsiantis, Christos Pierrakeas, Achilles Kameas

IEEE Access, 2021

A comparison of the optimized LSTM, XGBOOST and ARIMA in Time Series forecasting.

Iliana Paliari, Aikaterini Karanikola, Sotiris Kotsiantis

Proceedings of the 12th International Conference on Information, 2021

A comparative study of validity indices on estimating the optimal number of clusters.

Aikaterini Karanikola, Charalampos M. Liapis, Sotiris Kotsiantis

Proceedings of the 12th International Conference on Information, 2021

Applying Machine Learning to Predict Whether Learners Will Start a MOOC After Initial Registration.

Theodor Panagiotakopoulos, Sotiris Kotsiantis, Spiros A. Borotis, Fotis Lazarinis, Achilles Kameas

Proceedings of the Artificial Intelligence Applications and Innovations. AIAI 2021 IFIP WG 12.5 International Workshops, 2021

Active Bagging Ensemble Selection.

Vangjel Kazllarof, Sotiris Kotsiantis

Proceedings of the Artificial Intelligence Applications and Innovations. AIAI 2021 IFIP WG 12.5 International Workshops, 2021

2020

The Variability of the Reasons for Student Dropout in Distance Learning and the Prediction of Dropout-Prone Students.

Christos Pierrakeas, Giannis Koutsonikos, Anastasia-Dimitra Lipitakis, Sotiris Kotsiantis, Michalis Xenos, George A. Gravvanis

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.

Emmanuel Pintelas, Meletis Liaskos, Ioannis E. Livieris, Sotiris Kotsiantis, Panayiotis E. Pintelas

J. Imaging, 2020

Investigation of Combining Logitboost(M5P) under Active Learning Classification Tasks.

Vangjel Kazllarof, Stamatis Karlos, Sotiris Kotsiantis

Informatics, 2020

Polarity, emotions and online activity of students and tutors as features in predicting grades.

Andreas F. Gkontzis, Sotiris Kotsiantis, Dimitris Kalles, Christos T. Panagiotakopoulos, Vassilios S. Verykios

Intell. Decis. Technol., 2020

An active learning ensemble method for regression tasks.

Nikos Fazakis, Georgios Kostopoulos, Stamatis Karlos, Sotiris Kotsiantis, Kyriakos N. Sgarbas

Intell. Data Anal., 2020

Special issue on "Intelligent and fuzzy systems in data science and big data".

Stefania Tomasiello, Feng Feng, Sotiris Kotsiantis, Alireza Khastan

Evol. Intell., 2020

University students' intention to use search engines for research purposes: A structural equation modeling approach.

Konstantinos Lavidas, Anthi Achriani, Stavros Athanassopoulos, Ioannis Messinis, Sotiris Kotsiantis

Educ. Inf. Technol., 2020

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

Stamatis Karlos, Georgios Kostopoulos, Sotiris Kotsiantis

Algorithms, 2020

Iterative Robust Semi-Supervised Missing Data Imputation.

Nikos Fazakis, Georgios Kostopoulos, Sotiris Kotsiantis, Iosif Mporas

IEEE Access, 2020

Uncertainty Based Under-Sampling for Learning Naive Bayes Classifiers Under Imbalanced Data Sets.

Christos K. Aridas, Stamatis Karlos, Vasileios G. Kanas, Nikos Fazakis, Sotiris B. Kotsiantis

IEEE Access, 2020

An ensemble forecasting method using univariate time series COVID-19 data.

Charalampos M. Liapis, Aikaterini Karanikola, Sotiris Kotsiantis

Proceedings of the PCI 2020: 24th Pan-Hellenic Conference on Informatics, 2020

Active Hidden Naive Bayes.

Vangjel Kazllarof, Sotiris B. Kotsiantis

Proceedings of the PCI 2020: 24th Pan-Hellenic Conference on Informatics, 2020

2019

Multiview Learning for Early Prognosis of Academic Performance: A Case Study.

Georgios Kostopoulos, Stamatis Karlos, Sotiris Kotsiantis

IEEE Trans. Learn. Technol., 2019

A multi-scheme semi-supervised regression approach.

Nikos Fazakis, Stamatis Karlos, Sotiris Kotsiantis, Kyriakos N. Sgarbas

Pattern Recognit. Lett., 2019

Data preprocessing in predictive data mining.

Stamatios-Aggelos N. Alexandropoulos, Sotiris B. Kotsiantis, Michael N. Vrahatis

Knowl. Eng. Rev., 2019

A Semi-Supervised Regression Algorithm for Grade Prediction of Students in Distance Learning Courses.

Georgios Kostopoulos, Sotiris Kotsiantis, Nikos Fazakis, Giannis Koutsonikos, Christos Pierrakeas

Int. J. Artif. Intell. Tools, 2019

Hybrid local boosting utilizing unlabeled data in classification tasks.

Christos K. Aridas, Sotiris B. Kotsiantis, Michael N. Vrahatis

Evol. Syst., 2019

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

Nikos Fazakis, Vasileios G. Kanas, Christos K. Aridas, Stamatis Karlos, Sotiris Kotsiantis

Entropy, 2019

Active learning Rotation Forest for multiclass classification.

Vangjel Kazllarof, Stamatis Karlos, Sotiris Kotsiantis

Comput. Intell., 2019

A hybrid method for missing value imputation.

Aikaterini Karanikola, Sotiris Kotsiantis

Proceedings of the 23rd Pan-Hellenic Conference on Informatics, 2019

Performance Evaluation and Comparison of Multi-objective optimization Algorithms.

Dimitris G. Tsarmpopoulos, Athanasia N. Papanikolaou, Sotiris Kotsiantis, Theodoula N. Grapsa, George S. Androulakis

Proceedings of the 10th International Conference on Information, 2019

Financial Fraudulent Statements Detection through a Deep Dense Artificial Neural Network.

Georgios S. Temponeras, Stamatios-Aggelos N. Alexandropoulos, Sotiris B. Kotsiantis, Michael N. Vrahatis

Proceedings of the 10th International Conference on Information, 2019

Multi-objective Optimization of C4.5 Decision Tree for Predicting Student Academic Performance.

Georgios Kostopoulos, Nikos Fazakis, Sotiris Kotsiantis, Kyriakos N. Sgarbas

Proceedings of the 10th International Conference on Information, 2019

Combining Active Learning with Self-train algorithm for classification of multimodal problems.

Stamatis Karlos, Vasileios G. Kanas, Christos K. Aridas, Nikos Fazakis, Sotiris Kotsiantis

Proceedings of the 10th International Conference on Information, 2019

Self-trained eXtreme Gradient Boosting Trees.

Nikos Fazakis, Georgios Kostopoulos, Stamatis Karlos, Sotiris Kotsiantis, Kyriakos N. Sgarbas

Proceedings of the 10th International Conference on Information, 2019

Investigating the Benefits of Exploiting Incremental Learners Under Active Learning Scheme.

Stamatis Karlos, Vasileios G. Kanas, Nikos Fazakis, Christos K. Aridas, Sotiris Kotsiantis

Proceedings of the Artificial Intelligence Applications and Innovations, 2019

Stacking Strong Ensembles of Classifiers.

Stamatios-Aggelos N. Alexandropoulos, Christos K. Aridas, Sotiris B. Kotsiantis, Michael N. Vrahatis

Proceedings of the Artificial Intelligence Applications and Innovations, 2019

A Deep Dense Neural Network for Bankruptcy Prediction.

Stamatios-Aggelos N. Alexandropoulos, Christos K. Aridas, Sotiris B. Kotsiantis, Michael N. Vrahatis

Proceedings of the Engineering Applications of Neural Networks, 2019

2018

CST-Voting: A semi-supervised ensemble method for classification problems.

Georgios Kostopoulos, Ioannis E. Livieris, Sotiris B. Kotsiantis, Vassilis Tampakas

J. Intell. Fuzzy Syst., 2018

Semi-supervised regression: A recent review.

Georgios Kostopoulos, Stamatis Karlos, Sotiris Kotsiantis, Omiros Ragos

J. Intell. Fuzzy Syst., 2018

Forecasting students' success in an open university.

George Kostopoulos, Sotiris Kotsiantis, Christos Pierrakeas, Giannis Koutsonikos, George A. Gravvanis

Int. J. Learn. Technol., 2018

Optimized Active Learning Strategy for Audiovisual Speaker Recognition.

Stamatis Karlos, Konstantinos Kaleris, Nikos Fazakis, Vasileios G. Kanas, Sotiris Kotsiantis

Proceedings of the Speech and Computer - 20th International Conference, 2018

Local weighted Averaged 2-Dependence Estimator.

Stamatis Karlos, Aikaterini Karanikola, Vangjel Kazllarof, Sotiris Kotsiantis

Proceedings of the 10th Hellenic Conference on Artificial Intelligence, 2018

A Semi-supervised regressor based on model trees.

Nikos Fazakis, Stamatis Karlos, Sotiris Kotsiantis, Kyriakos N. Sgarbas

Proceedings of the 10th Hellenic Conference on Artificial Intelligence, 2018

An incrementally updateable ensemble learner.

Aikaterini Karanikola, Stamatis Karlos, Vangjel Kazllarof, Sotiris Kotsiantis

Proceedings of the 22nd Pan-Hellenic Conference on Informatics, 2018

An effective LA approach to predict student achievement.

Andreas F. Gkontzis, Sotiris Kotsiantis, Rozita Tsoni, Vassilios S. Verykios

Proceedings of the 22nd Pan-Hellenic Conference on Informatics, 2018

Predicting University Students' Grades Based on Previous Academic Achievements.

Maria Tsiakmaki, Georgios Kostopoulos, Giannis Koutsonikos, Christos Pierrakeas, Sotiris Kotsiantis, Omiros Ragos

Proceedings of the 9th International Conference on Information, 2018

Measuring Engagement to Assess Performance of Students in Distance Learning.

Andreas F. Gkontzis, Chris T. Panagiotakopoulos, Sotiris Kotsiantis, Vassilios S. Verykios

Proceedings of the 9th International Conference on Information, 2018

An incremental self-trained ensemble algorithm.

Stamatis Karlos, Nikos Fazakis, Konstantinos Kaleris, Vasileios G. Kanas, Sotiris Kotsiantis

Proceedings of the 2018 IEEE Conference on Evolving and Adaptive Intelligent Systems, 2018

Active fuzzy rule induction.

Aikaterini Karanikola, Stamatis Karlos, Vangjel Kazllarof, Eirini Kateri, Sotiris Kotsiantis

Proceedings of the 2018 IEEE Conference on Evolving and Adaptive Intelligent Systems, 2018

2017

Self-trained Rotation Forest for semi-supervised learning.

Nikos Fazakis, Stamatis Karlos, Sotiris Kotsiantis, Kyriakos N. Sgarbas

J. Intell. Fuzzy Syst., 2017

Students' evaluation of tutors in distance education: a quasi-longitudinal study.

Sotiris Kotsiantis, Nikolaos K. Tselios, Michalis Xenos

Int. J. Learn. Technol., 2017

Self-Trained Stacking Model for Semi-Supervised Learning.

Stamatis Karlos, Nikos Fazakis, Sotiris Kotsiantis, Kyriakos N. Sgarbas

Int. J. Artif. Intell. Tools, 2017

Locally application of naive Bayes for self-training.

Stamatis Karlos, Nikos Fazakis, Angeliki-Panagiota Panagopoulou, Sotiris Kotsiantis, Kyriakos N. Sgarbas

Evol. Syst., 2017

Automated hand gesture recognition exploiting Active Learning methods.

Vangjel Kazllarof, Stamatis Karlos, Sotiris Kotsiantis, Michalis Xenos

Proceedings of the 21st Pan-Hellenic Conference on Informatics, 2017

Enhancing high school students' performance based on semi-supervised methods.

Georgios Kostopoulos, Ioannis E. Livieris, Sotiris Kotsiantis, Vassilis Tampakas

Proceedings of the 8th International Conference on Information, 2017

Early dropout prediction in distance higher education using active learning.

Georgios Kostopoulos, Sotiris Kotsiantis, Omiros Ragos, Theodoula N. Grapsa

Proceedings of the 8th International Conference on Information, 2017

Predicting Student Performance in Distance Higher Education Using Active Learning.

Georgios Kostopoulos, Anastasia-Dimitra Lipitakis, Sotiris Kotsiantis, George A. Gravvanis

Proceedings of the Engineering Applications of Neural Networks, 2017

Using Active Learning Methods for Predicting Fraudulent Financial Statements.

Stamatis Karlos, Georgios Kostopoulos, Sotiris Kotsiantis, Vassilis Tampakas

Proceedings of the Engineering Applications of Neural Networks, 2017

Random Resampling in the One-Versus-All Strategy for Handling Multi-class Problems.

Christos K. Aridas, Stamatios-Aggelos N. Alexandropoulos, Sotiris B. Kotsiantis, Michael N. Vrahatis

Proceedings of the Engineering Applications of Neural Networks, 2017

A Prognosis of Junior High School Students' Performance Based on Active Learning Methods.

Georgios Kostopoulos, Sotiris Kotsiantis, Vassilios S. Verykios

Proceedings of the Brain Function Assessment in Learning - First International Conference, 2017

Evaluating Active Learning Methods for Bankruptcy Prediction.

Georgios Kostopoulos, Stamatis Karlos, Sotiris Kotsiantis, Vassilis Tampakas

Proceedings of the Brain Function Assessment in Learning - First International Conference, 2017

2016

Self-Trained LMT for Semisupervised Learning.

Nikos Fazakis, Stamatis Karlos, Sotiris B. Kotsiantis, Kyriakos N. Sgarbas

Comput. Intell. Neurosci., 2016

A Semisupervised Cascade Classification Algorithm.

Stamatis Karlos, Nikos Fazakis, Sotiris B. Kotsiantis, Kyriakos N. Sgarbas

Appl. Comput. Intell. Soft Comput., 2016

Speech Recognition Combining MFCCs and Image Features.

Stamatis Karlos, Nikos Fazakis, Katerina Karanikola, Sotiris B. Kotsiantis, Kyriakos N. Sgarbas

Proceedings of the Speech and Computer - 18th International Conference, 2016

Automated hand gesture recognition for educational applications.

Vangjel Kazllarof, Stamatis Karlos, Angeliki-Panagiota Panagopoulou, Sotiris Kotsiantis

Proceedings of the 20th Pan-Hellenic Conference on Informatics, 2016

Semi-supervised forecasting of fraudulent financial statements.

Stamatis Karlos, Nikos Fazakis, Sotiris Kotsiantis, Kyriakos N. Sgarbas

Proceedings of the 20th Pan-Hellenic Conference on Informatics, 2016

Effectiveness of semi-supervised learning in bankruptcy prediction.

Stamatis Karlos, Sotiris Kotsiantis, Nikos Fazakis, Kyriakos N. Sgarbas

Proceedings of the 7th International Conference on Information, 2016

Self-labeled Hidden Naive Bayes algorithm for semi-supervised classification.

Nikos Fazakis, Stamatis Karlos, Sotiris Kotsiantis, Kyriakos N. Sgarbas

Proceedings of the 7th International Conference on Information, 2016

Combining Prototype Selection with Local Boosting.

Christos K. Aridas, Sotiris B. Kotsiantis, Michael N. Vrahatis

Proceedings of the Artificial Intelligence Applications and Innovations, 2016

Increasing Diversity in Random Forests Using Naive Bayes.

Christos K. Aridas, Sotiris B. Kotsiantis, Michael N. Vrahatis

Proceedings of the Artificial Intelligence Applications and Innovations, 2016

2015

Speaker Identification Using Semi-supervised Learning.

Nikos Fazakis, Stamatis Karlos, Sotiris B. Kotsiantis, Kyriakos N. Sgarbas

Proceedings of the Speech and Computer - 17th International Conference, 2015

Estimating student dropout in distance higher education using semi-supervised techniques.

Georgios Kostopoulos, Sotiris B. Kotsiantis, Panagiotis E. Pintelas

Proceedings of the 19th Panhellenic Conference on Informatics, 2015

Combining random forest and support vector machines for semi-supervised learning.

Christos K. Aridas, Sotiris B. Kotsiantis

Proceedings of the 19th Panhellenic Conference on Informatics, 2015

Predicting Student Performance in Distance Higher Education Using Semi-supervised Techniques.

Georgios Kostopoulos, Sotiris B. Kotsiantis, Panagiotis E. Pintelas

Proceedings of the Model and Data Engineering - 5th International Conference, 2015

Combining ensembles algorithms of symbolic learners.

Anastasia-Dimitra Lipitakis, Sotiris Kotsiantis

Proceedings of the 6th International Conference on Information, 2015

Integrating global and local boosting.

Anastasia-Dimitra Lipitakis, Gerasimos S. Antzoulatos, Sotiris Kotsiantis, Michael N. Vrahatis

Proceedings of the 6th International Conference on Information, 2015

Self-Train LogitBoost for Semi-supervised Learning.

Stamatis Karlos, Nikos Fazakis, Sotiris B. Kotsiantis, Kyriakos N. Sgarbas

Proceedings of the Engineering Applications of Neural Networks, 2015

2014

Bagging and boosting variants for handling classifications problems: a survey.

Sotiris B. Kotsiantis

Knowl. Eng. Rev., 2014

Integrating global and local application of random subspace ensemble.

Sotiris B. Kotsiantis

J. Intell. Fuzzy Syst., 2014

A hybrid decision tree classifier.

Sotiris B. Kotsiantis

J. Intell. Fuzzy Syst., 2014

Integrating global and local application of naive bayes classifier.

Sotiris B. Kotsiantis

Int. Arab J. Inf. Technol., 2014

A hybrid Machine Learning methodology for imbalanced datasets.

Anastasia-Dimitra Lipitakis, Sotirios Kotsiantis

Proceedings of the 5th International Conference on Information, 2014

2013

Decision trees: a recent overview.

Sotiris B. Kotsiantis

Artif. Intell. Rev., 2013

2012

Evaluating and recommending Greek newspapers' websites using clustering.

Dimitris Kanellopoulos, Sotiris Kotsiantis

Program, 2012

Integrating Global and Local Voting of Classifiers.

Sotiris B. Kotsiantis

Cybern. Syst., 2012

Use of machine learning techniques for educational proposes: a decision support system for forecasting students' grades.

Sotiris B. Kotsiantis

Artif. Intell. Rev., 2012

Forecasting Fraudulent Financial Statements with Committee of Cost-Sensitive Decision Tree Classifiers.

Elias Zouboulidis, Sotiris B. Kotsiantis

Proceedings of the Artificial Intelligence: Theories and Applications, 2012

Credit Rating Using a Hybrid Voting Ensemble.

Elias Kamos, Foteini Matthaiou, Sotiris B. Kotsiantis

Proceedings of the Artificial Intelligence: Theories and Applications, 2012

Forecasting Corporate Bankruptcy with an Ensemble of Classifiers.

Despina Deligianni, Sotiris B. Kotsiantis

Proceedings of the Artificial Intelligence: Theories and Applications, 2012

Integrating Global and Local Application of Discriminative Multinomial Bayesian Classifier for Text Classification.

Emmanuel Pappas, Sotiris B. Kotsiantis

Proceedings of the Intelligent Informatics, 2012

2011

Intelligent Systems and Knowledge Management (Part II).

Dimitris Kanellopoulos, Sotiris B. Kotsiantis, Panayiotis E. Pintelas

J. Comput. Methods Sci. Eng., 2011

A random subspace method that uses different instead of similar models for regression and classification problems.

Sotiris B. Kotsiantis

Int. J. Inf. Decis. Sci., 2011

Cascade Generalization with Reweighting Data for Handling Imbalanced Problems.

Sotiris B. Kotsiantis

Comput. J., 2011

An incremental ensemble of classifiers.

Sotiris B. Kotsiantis

Artif. Intell. Rev., 2011

Combining bagging, boosting, rotation forest and random subspace methods.

Sotiris B. Kotsiantis

Artif. Intell. Rev., 2011

2010

A combinational incremental ensemble of classifiers as a technique for predicting students' performance in distance education.

Sotiris B. Kotsiantis, Kiriakos Patriarcheas, Michalis Nik Xenos

Knowl. Based Syst., 2010

Financial Application of Multi-Instance Learning: Two Greek Case Studies.

Sotiris B. Kotsiantis, Dimitris Kanellopoulos, Vasilis Tampakas

J. Convergence Inf. Technol., 2010

Local rotation-based ensemble.

Sotiris B. Kotsiantis

Int. J. Knowl. Eng. Data Min., 2010

Rotation-based model trees for classification.

Sotiris B. Kotsiantis

Int. J. Data Anal. Tech. Strateg., 2010

Bagging different instead of similar models for regression and classification problems.

Sotiris B. Kotsiantis, Dimitris N. Kanellopoulos

Int. J. Comput. Appl. Technol., 2010

Cascade generalisation for ordinal problems.

Sotiris B. Kotsiantis, Dimitris Kanellopoulos

Int. J. Artif. Intell. Soft Comput., 2010

2009

Educational data mining: a case study for predicting dropout-prone students.

Sotiris B. Kotsiantis

Int. J. Knowl. Eng. Soft Data Paradigms, 2009

Selective costing ensemble for handling imbalanced data sets.

Sotiris B. Kotsiantis, Panayiotis E. Pintelas

Int. J. Hybrid Intell. Syst., 2009

Locally application of random subspace with simple Bayesian classifier.

Sotiris B. Kotsiantis

Int. J. Data Min. Model. Manag., 2009

2008

Handling imbalanced data sets with a modification of Decorate algorithm.

Sotiris B. Kotsiantis

Int. J. Comput. Appl. Technol., 2008

Local reweight wrapper for the problem of imbalance.

Sotiris B. Kotsiantis

Int. J. Artif. Intell. Soft Comput., 2008

Locally application of cascade generalization for classification problems.

Sotiris B. Kotsiantis

Intell. Decis. Technol., 2008

Stacking Cost Sensitive Models.

Sotiris B. Kotsiantis

Proceedings of the Panhellenic Conference on Informatics, 2008

Local Grading of Learners.

Sotiris B. Kotsiantis

Proceedings of the Panhellenic Conference on Informatics, 2008

Applying Machine Learning Techniques for Environmental Reporting.

Sotiris B. Kotsiantis, Dimitris Kanellopoulos

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.

Sotiris B. Kotsiantis

Proceedings of the Emerging Artificial Intelligence Applications in Computer Engineering, 2007

Selective costing voting for bankruptcy prediction.

Sotiris B. Kotsiantis, Dimitris Tzelepis, Euaggelos Koumanakos, Vasilis Tampakas

Int. J. Knowl. Based Intell. Eng. Syst., 2007

Supervised Machine Learning: A Review of Classification Techniques.

Sotiris B. Kotsiantis

Informatica (Slovenia), 2007

Credit risk analysis using a hybrid data mining model.

Sotiris B. Kotsiantis

Int. J. Intell. Syst. Technol. Appl., 2007

Combining Bagging, Boosting and Dagging for Classification Problems.

Sotiris B. Kotsiantis, Dimitris Kanellopoulos

Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2007

A Wrapper for Reweighting Training Instances for Handling Imbalanced Data Sets.

M. Karagiannopoulos, D. Anyfantis, Sotiris B. Kotsiantis, Panayiotis E. Pintelas

Proceedings of the Artificial Intelligence and Innovations 2007: from Theory to Applications, 2007

Robustness of learning techniques in handling class noise in imbalanced datasets.

D. Anyfantis, M. Karagiannopoulos, Sotiris B. Kotsiantis, Panayiotis E. Pintelas

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.

Dimitris Kanellopoulos, Sotiris B. Kotsiantis, Vasilis Tampakas

Proceedings of 12th IEEE International Conference on Emerging Technologies and Factory Automation, 2007

2006

Local Boosting of Decision Stumps for Regression and Classification Problems.

Sotiris B. Kotsiantis, Dimitris Kanellopoulos, Panayiotis E. Pintelas

J. Comput., 2006

Local averaging of heterogeneous regression models.

Sotiris B. Kotsiantis

Int. J. Hybrid Intell. Syst., 2006

Machine learning: a review of classification and combining techniques.

Sotiris B. Kotsiantis, Ioannis D. Zaharakis, Panayiotis E. Pintelas

Artif. Intell. Rev., 2006

Predicting Fraudulent Financial Statements with Machine Learning Techniques.

Sotiris B. Kotsiantis, Euaggelos Koumanakos, Dimitris Tzelepis, Vasilis Tampakas

Proceedings of the Advances in Artificial Intelligence, 4th Helenic Conference on AI, 2006

Local Additive Regression of Decision Stumps.

Sotiris B. Kotsiantis, Dimitris Kanellopoulos, Panayiotis E. Pintelas

Proceedings of the Advances in Artificial Intelligence, 4th Helenic Conference on AI, 2006

Bagged Averaging of Regression Models.

Sotiris B. Kotsiantis, Dimitris Kanellopoulos, Ioannis D. Zaharakis

Proceedings of the Artificial Intelligence Applications and Innovations, 2006

Local Ordinal Classification.

Sotiris B. Kotsiantis

Proceedings of the Artificial Intelligence Applications and Innovations, 2006

Financial Application of Neural Networks: Two Case Studies in Greece.

Sotiris B. Kotsiantis, Euaggelos Koumanakos, Dimitris Tzelepis, Vasilis Tampakas

Proceedings of the Artificial Neural Networks, 2006

Ontology-based Learning Applications: A Development Methodology.

Dimitris Kanellopoulos, Sotiris B. Kotsiantis, Panayiotis E. Pintelas

Proceedings of the IASTED International Conference on Software Engineering, 2006

2005

Local voting of weak classifiers.

Sotiris B. Kotsiantis, Panayiotis E. Pintelas

Int. J. Knowl. Based Intell. Eng. Syst., 2005

Logitboost of Simple Bayesian Classifier.

Sotiris B. Kotsiantis, Panayiotis E. Pintelas

Informatica (Slovenia), 2005

Bagging Model Trees for Classification Problems.

Sotiris B. Kotsiantis, George E. Tsekouras, Panayiotis E. Pintelas

Proceedings of the Advances in Informatics, 2005

Modeling the Organoleptic Properties of Matured Wine Distillates.

Sotiris B. Kotsiantis, George E. Tsekouras, C. Raptis, Panayiotis E. Pintelas

Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2005

Bagging Random Trees for Estimation of Tissue Softness.

Sotiris B. Kotsiantis, George E. Tsekouras, Panayiotis E. Pintelas

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.

George E. Tsekouras, Dimitris Papageorgiou, Sotiris B. Kotsiantis, Christos Kalloniatis, Panayiotis E. Pintelas

Proceedings of the Innovations in Applied Artificial Intelligence, 2005

Local Bagging of Decision Stumps.

Sotiris B. Kotsiantis, George E. Tsekouras, Panayiotis E. Pintelas

Proceedings of the Innovations in Applied Artificial Intelligence, 2005

Predicting Students' Marks in Hellenic Open University.

Sotiris B. Kotsiantis, Panayiotis E. Pintelas

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.

Sotiris B. Kotsiantis, Panayiotis E. Pintelas

Interact. Technol. Smart Educ., 2004

Predicting Students' Performance In Distance Learning Using Machine Learning Techniques.

Sotiris B. Kotsiantis, Christos Pierrakeas, Panayiotis E. Pintelas

Appl. Artif. Intell., 2004

A Cost Sensitive Technique for Ordinal Classification Problems.

Sotiris B. Kotsiantis, Panayiotis E. Pintelas

Proceedings of the Methods and Applications of Artificial Intelligence, 2004

An Online Ensemble of Classifiers.

Sotiris B. Kotsiantis, Panayiotis E. Pintelas

Proceedings of the Pattern Recognition in Information Systems, 2004

Fuzzy Clustering of Categorical Attributes and its Use in Analyzing Cultural Data.

George E. Tsekouras, Dimitris Papageorgiou, Sotiris B. Kotsiantis, Christos Kalloniatis, Panayiotis E. Pintelas

Proceedings of the International Conference on Computational Intelligence, 2004

A Hybrid Decision Support Tool - Using Ensemble of Classifiers.

Sotiris B. Kotsiantis, Panayiotis E. Pintelas

Proceedings of the ICEIS 2004, 2004

Increasing the Classification Accuracy of Simple Bayesian Classifier.

Sotiris B. Kotsiantis, Panayiotis E. Pintelas

Proceedings of the Artificial Intelligence: Methodology, 2004

Bagged Voting Ensembles.

Sotiris B. Kotsiantis, Panayiotis E. Pintelas

Proceedings of the Artificial Intelligence: Methodology, 2004

2003

Preventing Student Dropout in Distance Learning Using Machine Learning Techniques.

Sotiris B. Kotsiantis, Christos Pierrakeas, Panayiotis E. Pintelas

Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2003