Supervised machine learning: A review of classification techniques SB Kotsiantis, I Zaharakis, P Pintelas Emerging artificial intelligence applications in computer engineering 160 (1 …, 2007 | 7581 | 2007 |
Machine learning: a review of classification and combining techniques SB Kotsiantis, ID Zaharakis, PE Pintelas Artificial Intelligence Review 26, 159-190, 2006 | 1720 | 2006 |
Data preprocessing for supervised leaning SB Kotsiantis, D Kanellopoulos, PE Pintelas International journal of computer science 1 (2), 111-117, 2006 | 1524 | 2006 |
Handling imbalanced datasets: A review S Kotsiantis, D Kanellopoulos, P Pintelas GESTS international transactions on computer science and engineering 30 (1 …, 2006 | 1372 | 2006 |
A CNN–LSTM model for gold price time-series forecasting IE Livieris, E Pintelas, P Pintelas Neural computing and applications 32, 17351-17360, 2020 | 631 | 2020 |
A survey on student dropout rates and dropout causes concerning the students in the Course of Informatics of the Hellenic Open University M Xenos, C Pierrakeas, P Pintelas Computers & Education 39 (4), 361-377, 2002 | 431 | 2002 |
PREDICTING STUDENTS'PERFORMANCE IN DISTANCE LEARNING USING MACHINE LEARNING TECHNIQUES S Kotsiantis, C Pierrakeas, P Pintelas Applied Artificial Intelligence 18 (5), 411-426, 2004 | 413 | 2004 |
Preventing student dropout in distance learning using machine learning techniques SB Kotsiantis, CJ Pierrakeas, PE Pintelas Knowledge-Based Intelligent Information and Engineering Systems: 7th …, 2003 | 380 | 2003 |
Recent advances in clustering: A brief survey S Kotsiantis, P Pintelas WSEAS Transactions on Information Science and Applications 1 (1), 73-81, 2004 | 319 | 2004 |
Combining bagging and boosting S Kotsiantis, P Pintelas International Journal of Computational Intelligence 1 (4), 324-333, 2004 | 209 | 2004 |
Mixture of expert agents for handling imbalanced data sets SB Kotsiantis, PE Pintelas Annals of Mathematics, Computing & Teleinformatics 1 (1), 46-55, 2003 | 196 | 2003 |
Predicting students marks in hellenic open university SB Kotsiantis, PE Pintelas fifth IEEE international conference on advanced learning technologies (ICALT …, 2005 | 140 | 2005 |
An Advanced CNN-LSTM Model for Cryptocurrency Forecasting. Electronics 2021, 10, 287 IE Livieris, N Kiriakidou, S Stavroyiannis, P Pintelas s Note: MDPI stays neu-tral with regard to jurisdictional clai-ms in …, 2021 | 135* | 2021 |
Ensemble deep learning models for forecasting cryptocurrency time-series IE Livieris, E Pintelas, S Stavroyiannis, P Pintelas Algorithms 13 (5), 121, 2020 | 131 | 2020 |
A grey-box ensemble model exploiting black-box accuracy and white-box intrinsic interpretability E Pintelas, IE Livieris, P Pintelas Algorithms 13 (1), 17, 2020 | 129 | 2020 |
Predicting secondary school students' performance utilizing a semi-supervised learning approach IE Livieris, K Drakopoulou, VT Tampakas, TA Mikropoulos, P Pintelas Journal of educational computing research 57 (2), 448-470, 2019 | 111 | 2019 |
Logitboost of simple bayesian classifier SB Kotsiantis Informatica 29 (1), 2005 | 90 | 2005 |
Feature selection for regression problems M Karagiannopoulos, D Anyfantis, SB Kotsiantis, PE Pintelas Proceedings of the 8th Hellenic European Research on Computer Mathematics …, 2007 | 85 | 2007 |
Investigating the problem of cryptocurrency price prediction: a deep learning approach E Pintelas, IE Livieris, S Stavroyiannis, T Kotsilieris, P Pintelas Artificial Intelligence Applications and Innovations: 16th IFIP WG 12.5 …, 2020 | 79 | 2020 |
Predicting students' performance using artificial neural networks IE Livieris, K Drakopoulou, P Pintelas Συνέδρια της Ελληνικής Επιστημονικής Ένωσης Τεχνολογιών Πληροφορίας …, 2012 | 75 | 2012 |