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Sotiris B. Kotsiantis Sotiris Kotsiantis Sotirios Kotsiantis http://www.math.upatras.gr/~sotos/ https://scholar.google.com/citations?user=h6zwXYMAAAAJ https://zbmath.org/authors/?q=ai:kotsiantis.sotiris-b https://orcid.org/0000-0002-2247-3082 https://www.wikidata.org/entity/Q66771622 https://ieeexplore.ieee.org/author/37294564900 University of Patras, Greece
Andreas F. Gkontzis Sotiris Kotsiantis Georgios Feretzakis Vassilios S. Verykios Temporal Dynamics of Citizen-Reported Urban Challenges: A Comprehensive Time Series Analysis. 27 2024 March 8 Big Data Cogn. Comput. 3 https://doi.org/10.3390/bdcc8030027 db/journals/bdcc/bdcc8.html#GkontzisKFV24
Andreas F. Gkontzis Sotiris Kotsiantis Georgios Feretzakis Vassilios S. Verykios Enhancing Urban Resilience: Smart City Data Analyses, Forecasts, and Digital Twin Techniques at the Neighborhood Level. 47 2024 February 16 Future Internet 2 https://doi.org/10.3390/fi16020047 db/journals/fi/fi16.html#GkontzisKFV24
Aristidis G. Vrahatis Konstantinos Lazaros Sotiris Kotsiantis Graph Attention Networks: A Comprehensive Review of Methods and Applications. 318 2024 September 16 Future Internet 9 https://doi.org/10.3390/fi16090318 db/journals/fi/fi16.html#VrahatisLK24 streams/journals/fi
Konstantinos Lazaros Dimitris E. Koumadorakis Aristidis G. Vrahatis Sotiris Kotsiantis A comprehensive review on zero-shot-learning techniques. 1001-1028 2024 18 Intell. Decis. Technol. 2 https://doi.org/10.3233/IDT-240297 db/journals/idt/idt18.html#LazarosKVK24
Pantelis Linardatos Vasilis Papastefanopoulos Sotiris Kotsiantis Regressor cascading for time series forecasting. 1139-1156 2024 18 Intell. Decis. Technol. 2 https://doi.org/10.3233/IDT-240224 db/journals/idt/idt18.html#LinardatosPK24
Anastasia-Dimitra Lipitakis George A. Gravvanis Christos K. Filelis-Papadopoulos Sotiris Kotsiantis Dimosthenis Anagnostopoulos Sparse Approximate Pseudoinverse Preconditioning for Sparse Supervised Learning Problems with More Features than Samples. 2450011:1-2450011:22 2024 June 33 Int. J. Artif. Intell. Tools 4 https://doi.org/10.1142/S0218213024500118 db/journals/ijait/ijait33.html#LipitakisGFKA24 streams/journals/ijait
Charalampos M. Liapis Aikaterini Karanikola Sotiris Kotsiantis Emotion-Driven Energy Load Forecasting: An Ensemble Leveraging Insights from News. 2450013:1-2450013:19 2024 August 33 Int. J. Artif. Intell. Tools 5 https://doi.org/10.1142/S0218213024500131 db/journals/ijait/ijait33.html#LiapisKK24 streams/journals/ijait
Charalampos M. Liapis Aikaterini Karanikola Sotiris Kotsiantis Data-efficient software defect prediction: A comparative analysis of active learning-enhanced models and voting ensembles. 120786 2024 676 Inf. Sci. https://doi.org/10.1016/j.ins.2024.120786 db/journals/isci/isci676.html#LiapisKK24
Vassilios S. Verykios Evgenia Paxinou Aris Gkoulalas-Divanis Manolis Tzagarakis Sotirios Kotsiantis Georgios Feretzakis Dimitris Kalles The Faculty Assignment Problem in Higher Education: A Shapley Value-Based Approach. 224-237 2024 AIAI (4) https://doi.org/10.1007/978-3-031-63223-5_17 conf/ifip12/2024aiai4 db/conf/ifip12/aiai2024-4.html#VerykiosPGTKFK24
Emmanuel Pintelas Ioannis E. Livieris Sotiris Kotsiantis Panayiotis E. Pintelas A multi-view-CNN framework for deep representation learning in image classification. 103687 2023 July 232 Comput. Vis. Image Underst. https://doi.org/10.1016/j.cviu.2023.103687 db/journals/cviu/cviu232.html#PintelasLKP23
Charalampos M. Liapis Aikaterini Karanikola Sotiris Kotsiantis Investigating Deep Stock Market Forecasting with Sentiment Analysis. 219 2023 February 25 Entropy 2 https://doi.org/10.3390/e25020219 db/journals/entropy/entropy25.html#LiapisKK23
Aikaterini Karanikola Gregory Davrazos Charalampos M. Liapis Sotiris Kotsiantis Financial sentiment analysis: Classic methods vs. deep learning models. 893-915 2023 17 Intell. Decis. Technol. 4 https://doi.org/10.3233/IDT-230478 db/journals/idt/idt17.html#KaranikolaDLK23
Athanasios I. Salamanis George A. Gravvanis Sotiris B. Kotsiantis Michael N. Vrahatis Novel Sparse Feature Regression Method for Traffic Forecasting. 2350008:1-2350008:27 2023 February 32 Int. J. Artif. Intell. Tools 1 https://doi.org/10.1142/S0218213023500082 db/journals/ijait/ijait32.html#SalamanisGKV23
Charalampos M. Liapis Sotiris Kotsiantis Temporal Convolutional Networks and BERT-Based Multi-Label Emotion Analysis for Financial Forecasting. 596 2023 14 Inf. 11 https://doi.org/10.3390/info14110596 db/journals/information/information14.html#LiapisK23
Athanasios I. Salamanis George A. Gravvanis Sotiris Kotsiantis Konstantinos M. Giannoutakis A generic sparse regression imputation method for time series and tabular data. 110965 2023 November 279 Knowl. Based Syst. https://doi.org/10.1016/j.knosys.2023.110965 db/journals/kbs/kbs279.html#SalamanisGKG23
Stamatis Karlos Christos K. Aridas Vasileios G. Kanas Sotiris Kotsiantis Classification of acoustical signals by combining active learning strategies with semi-supervised learning schemes. 3-20 2023 35 Neural Comput. Appl. 1 https://doi.org/10.1007/s00521-021-05749-6 db/journals/nca/nca35.html#KarlosAKK23
Charalampos M. Liapis Aikaterini Karanikola Sotiris Kotsiantis A multivariate ensemble learning method for medium-term energy forecasting. 21479-21497 2023 October 35 Neural Comput. Appl. 29 https://doi.org/10.1007/s00521-023-08777-6 db/journals/nca/nca35.html#LiapisKK23
Panagiotis E. Pintelas Sotiris Kotsiantis Ioannis E. Livieris Special Issue on Machine Learning and AI for Sensors. 2770 2023 March 23 Sensors 5 https://doi.org/10.3390/s23052770 db/journals/sensors/sensors23.html#PintelasKL23
Vangjel Kazllarof Sotiris Kotsiantis Active Learning Query Strategy Selection Using Dataset Meta-features Extraction. 185-194 2023 AIAI (2) https://doi.org/10.1007/978-3-031-34107-6_15 conf/ifip12/2023aiai2 db/conf/ifip12/aiai2023-2.html#KazllarofK23 Gregory Davrazos Theodor Panagiotakopoulos Sotiris Kotsiantis Water Quality Estimation from IoT Sensors Using a Meta-ensemble. 393-403 2023 AIAI Workshops https://doi.org/10.1007/978-3-031-34171-7_32 conf/ifip12/2023aiaiw db/conf/ifip12/aiai2023w.html#DavrazosPK23 Gregory Davrazos Theodor Panagiotakopoulos Sotiris Kotsiantis Achilles Kameas Predicting Cost of Municipal Waste Management using IoT Data and Machine Learning. 1-4 2023 IISA https://doi.org/10.1109/IISA59645.2023.10345856 conf/iisa/2023 db/conf/iisa/iisa2023.html#DavrazosPKK23 Gregory Davrazos Theodor Panagiotakopoulos Sotiris Kotsiantis Achilles Kameas Android Malware Detection in IoT Mobile Devices using a Meta-ensemble Classifier. 1-4 2023 IISA https://doi.org/10.1109/IISA59645.2023.10345858 conf/iisa/2023 db/conf/iisa/iisa2023.html#DavrazosPKK23a Gregory Davrazos Theodor Panagiotakopoulos Sotiris Kotsiantis Achilles Kameas IoT Device Identification Using a Meta-Ensemble Multi-Class Classifier. 1-4 2023 IISA https://doi.org/10.1109/IISA59645.2023.10345911 conf/iisa/2023 db/conf/iisa/iisa2023.html#DavrazosPKK23b Gregory Davrazos Theodor Panagiotakopoulos Sotiris Kotsiantis Achilles Kameas IoT-Enabled Crop Recommendation in Smart Agriculture Using Machine Learning. 1-4 2023 IISA https://doi.org/10.1109/IISA59645.2023.10345924 conf/iisa/2023 db/conf/iisa/iisa2023.html#DavrazosPKK23c
Nikolaos S. Alachiotis Sotiris Kotsiantis Evangelos Sakkopoulos Vassilios S. Verykios Supervised machine learning models for student performance prediction. 93-106 2022 16 Intell. Decis. Technol. 1 https://doi.org/10.3233/IDT-210251 db/journals/idt/idt16.html#AlachiotisKSV22
Stamatios-Aggelos N. Alexandropoulos Christos K. Aridas Sotiris B. Kotsiantis George A. Gravvanis Michael N. Vrahatis Rotation forest of random subspace models. 315-324 2022 16 Intell. Decis. Technol. 2 https://doi.org/10.3233/IDT-210074 db/journals/idt/idt16.html#Alexandropoulos22
Andreas F. Gkontzis Sotiris Kotsiantis Christos T. Panagiotakopoulos Vassilios S. Verykios A predictive analytics framework as a countermeasure for attrition of students. 568-582 2022 30 Interact. Learn. Environ. 3 https://doi.org/10.1080/10494820.2019.1674884 db/journals/ile/ile30.html#GontzisKPV22
Andreas F. Gkontzis Sotiris Kotsiantis Christos T. Panagiotakopoulos Vassilios S. Verykios A predictive analytics framework as a countermeasure for attrition of students. 1028-1043 2022 30 Interact. Learn. Environ. 6 https://doi.org/10.1080/10494820.2019.1709209 db/journals/ile/ile30.html#GkontzisKPV22
Georgia Garani Dionysios Papadatos Sotiris Kotsiantis Vassilios S. Verykios Meteorological Data Warehousing and Analysis for Supporting Air Navigation. 78 2022 December 9 Informatics 4 https://doi.org/10.3390/informatics9040078 db/journals/informatics/informatics9.html#GaraniPKV22
Charalampos M. Liapis Aikaterini Karanikola Sotiris Kotsiantis Energy Load Forecasting: Investigating Mid-Term Predictions with Ensemble Learners. 343-355 2022 AIAI (1) https://doi.org/10.1007/978-3-031-08333-4_28 conf/ifip12/2022aiai1 db/conf/ifip12/aiai2022-1.html#LiapisKK22 Panos K. Syriopoulos Sotiris B. Kotsiantis Michael N. Vrahatis Survey on KNN Methods in Data Science. 379-393 2022 LION https://doi.org/10.1007/978-3-031-24866-5_28 conf/lion/2022 db/conf/lion/lion2022.html#SyriopoulosKV22 Charalampos M. Liapis Sotiris Kotsiantis Energy Balance Forecasting: An Extensive Multivariate Regression Models Comparison. 41:1-41:7 2022 SETN https://doi.org/10.1145/3549737.3549782 conf/setn/2022 db/conf/setn/setn2022.html#LiapisK22 Vangjel Kazllarof Sotiris Kotsiantis Human Activity Recognition using Time Series Feature Extraction and Active Learning. 46:1-46:4 2022 SETN https://doi.org/10.1145/3549737.3549787 conf/setn/2022 db/conf/setn/setn2022.html#KazllarofK22
Georgios Kostopoulos Theodor Panagiotakopoulos Sotiris Kotsiantis Christos Pierrakeas Achilles Kameas Interpretable Models for Early Prediction of Certification in MOOCs: A Case Study on a MOOC for Smart City Professionals. 165881-165891 2021 9 IEEE Access https://doi.org/10.1109/ACCESS.2021.3134787 db/journals/access/access9.html#KostopoulosPKPK21
Pantelis Linardatos Vasilis Papastefanopoulos Sotiris Kotsiantis Explainable AI: A Review of Machine Learning Interpretability Methods. 18 2021 23 Entropy 1 https://doi.org/10.3390/e23010018 https://www.wikidata.org/entity/Q104614812 db/journals/entropy/entropy23.html#LinardatosPK21
Charalampos M. Liapis Aikaterini Karanikola Sotiris Kotsiantis A Multi-Method Survey on the Use of Sentiment Analysis in Multivariate Financial Time Series Forecasting. 1603 2021 23 Entropy 12 https://doi.org/10.3390/e23121603 db/journals/entropy/entropy23.html#LiapisKK21
Athanasios I. Salamanis Anastasia-Dimitra Lipitakis George A. Gravvanis Sotiris Kotsiantis Dimosthenis Anagnostopoulos An adaptive cluster-based sparse autoregressive model for large-scale multi-step traffic forecasting. 115093 2021 180 Expert Syst. Appl. https://doi.org/10.1016/j.eswa.2021.115093 db/journals/eswa/eswa180.html#SalamanisLGKA21
Aikaterini Karanikola Charalampos M. Liapis Sotiris Kotsiantis Investigating cluster validation metrics for optimal number of clusters determination. 809-824 2021 15 Intell. Decis. Technol. 4 https://doi.org/10.3233/IDT-210187 db/journals/idt/idt15.html#KaranikolaLK21
Maria Tsiakmaki Georgios Kostopoulos Sotiris Kotsiantis Omiros Ragos Fuzzy-based active learning for predicting student academic performance using autoML: a step-wise approach. 635-667 2021 33 J. Comput. High. Educ. 3 https://doi.org/10.1007/s12528-021-09279-x db/journals/jche/jche33.html#TsiakmakiKKR21
Emmanuel Pintelas Meletis Liaskos Ioannis E. Livieris Sotiris Kotsiantis Panagiotis E. Pintelas A novel explainable image classification framework: case study on skin cancer and plant disease prediction. 15171-15189 2021 33 Neural Comput. Appl. 22 https://doi.org/10.1007/s00521-021-06141-0 db/journals/nca/nca33.html#PintelasLLKP21
Gautam Srivastava 0001 Jerry Chun-Wei Lin Dragan Pamucar Sotiris Kotsiantis Editorial: Applications of Fuzzy Systems in Data Science and Big Data. 1-3 2021 29 IEEE Trans. Fuzzy Syst. 1 https://doi.org/10.1109/TFUZZ.2020.3039398 db/journals/tfs/tfs29.html#SrivastavaLPK21
Vangjel Kazllarof Sotiris Kotsiantis Active Bagging Ensemble Selection. 455-465 2021 AIAI Workshops https://doi.org/10.1007/978-3-030-79157-5_37 conf/ifip12/2021aiaiw db/conf/ifip12/aiai2021w.html#KazllarofK21 Theodor Panagiotakopoulos Sotiris Kotsiantis Spiros A. Borotis Fotis Lazarinis Achilles Kameas Applying Machine Learning to Predict Whether Learners Will Start a MOOC After Initial Registration. 466-475 2021 AIAI Workshops https://doi.org/10.1007/978-3-030-79157-5_38 conf/ifip12/2021aiaiw db/conf/ifip12/aiai2021w.html#Panagiotakopoulos21 Aikaterini Karanikola Charalampos M. Liapis Sotiris Kotsiantis A comparative study of validity indices on estimating the optimal number of clusters. 1-8 2021 IISA https://doi.org/10.1109/IISA52424.2021.9555497 conf/iisa/2021 db/conf/iisa/iisa2021.html#KaranikolaLK21 Iliana Paliari Aikaterini Karanikola Sotiris Kotsiantis A comparison of the optimized LSTM, XGBOOST and ARIMA in Time Series forecasting. 1-7 2021 IISA https://doi.org/10.1109/IISA52424.2021.9555520 conf/iisa/2021 db/conf/iisa/iisa2021.html#PaliariKK21
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. 2122-2133 2020 8 IEEE Access https://doi.org/10.1109/ACCESS.2019.2961784 db/journals/access/access8.html#AridasKKFK20
Nikos Fazakis Georgios Kostopoulos Sotiris Kotsiantis Iosif Mporas Iterative Robust Semi-Supervised Missing Data Imputation. 90555-90569 2020 8 IEEE Access https://doi.org/10.1109/ACCESS.2020.2994033 db/journals/access/access8.html#FazakisKKM20
Stamatis Karlos Georgios Kostopoulos Sotiris Kotsiantis A Soft-Voting Ensemble Based Co-Training Scheme Using Static Selection for Binary Classification Problems. 26 2020 13 Algorithms 1 https://doi.org/10.3390/a13010026 db/journals/algorithms/algorithms13.html#KarlosKK20
Konstantinos Lavidas Anthi Achriani Stavros Athanassopoulos Ioannis Messinis Sotiris Kotsiantis University students' intention to use search engines for research purposes: A structural equation modeling approach. 2463-2479 2020 25 Educ. Inf. Technol. 4 https://doi.org/10.1007/s10639-019-10071-9 db/journals/eait/eait25.html#LavidasAAMK20
Stefania Tomasiello Feng Feng 0003 Sotiris Kotsiantis Alireza Khastan Special issue on "Intelligent and fuzzy systems in data science and big data". 131 2020 13 Evol. Intell. 2 https://doi.org/10.1007/s12065-020-00423-7 db/journals/evi/evi13.html#TomasielloFKK20
Nikos Fazakis Georgios Kostopoulos Stamatis Karlos Sotiris Kotsiantis Kyriakos N. Sgarbas An active learning ensemble method for regression tasks. 607-623 2020 24 Intell. Data Anal. 3 https://doi.org/10.3233/IDA-194608 db/journals/ida/ida24.html#FazakisKKKS20
Andreas F. Gkontzis Sotiris Kotsiantis Dimitris Kalles Christos T. Panagiotakopoulos Vassilios S. Verykios Polarity, emotions and online activity of students and tutors as features in predicting grades. 409-436 2020 14 Intell. Decis. Technol. 3 https://doi.org/10.3233/IDT-190137 db/journals/idt/idt14.html#GkontzisKKPV20
Vangjel Kazllarof Stamatis Karlos Sotiris Kotsiantis Investigation of Combining Logitboost(M5P) under Active Learning Classification Tasks. 50 2020 7 Informatics 4 https://doi.org/10.3390/informatics7040050 db/journals/informatics/informatics7.html#KazllarofKK20
Emmanuel Pintelas Meletis Liaskos Ioannis E. Livieris Sotiris Kotsiantis Panayiotis E. Pintelas Explainable Machine Learning Framework for Image Classification Problems: Case Study on Glioma Cancer Prediction. 37 2020 6 J. Imaging 6 https://doi.org/10.3390/jimaging6060037 db/journals/jimaging/jimaging6.html#PintelasLLKP20
Vangjel Kazllarof Sotiris B. Kotsiantis Active Hidden Naive Bayes. 38-41 2020 PCI https://doi.org/10.1145/3437120.3437270 conf/pci/2020 db/conf/pci/pci2020.html#KazllarofK20 Charalampos M. Liapis Aikaterini Karanikola Sotiris Kotsiantis An ensemble forecasting method using univariate time series COVID-19 data. 50-52 2020 PCI https://doi.org/10.1145/3437120.3437273 conf/pci/2020 db/conf/pci/pci2020.html#LiapisKK20 Christos Pierrakeas Giannis Koutsonikos Anastasia-Dimitra Lipitakis Sotiris Kotsiantis Michalis Xenos George A. Gravvanis The Variability of the Reasons for Student Dropout in Distance Learning and the Prediction of Dropout-Prone Students. 91-111 2020 Machine Learning Paradigms https://doi.org/10.1007/978-3-030-13743-4_6 series/isrl/158 db/series/isrl/isrl158.html#PierrakeasKLKXG20
Vangjel Kazllarof Stamatis Karlos Sotiris Kotsiantis Active learning Rotation Forest for multiclass classification. 891-918 2019 35 Comput. Intell. 4 https://doi.org/10.1111/coin.12217 db/journals/ci/ci35.html#KazllarofKK19
Nikos Fazakis Vasileios G. Kanas Christos K. Aridas Stamatis Karlos Sotiris Kotsiantis Combination of Active Learning and Semi-Supervised Learning under a Self-Training Scheme. 988 2019 21 Entropy 10 https://doi.org/10.3390/e21100988 db/journals/entropy/entropy21.html#FazakisKAKK19
Christos K. Aridas Sotiris B. Kotsiantis Michael N. Vrahatis Hybrid local boosting utilizing unlabeled data in classification tasks. 51-61 2019 10 Evol. Syst. 1 https://doi.org/10.1007/s12530-017-9203-y https://www.wikidata.org/entity/Q66800063 db/journals/evs/evs10.html#AridasKV19
Georgios Kostopoulos Sotiris Kotsiantis Nikos Fazakis Giannis Koutsonikos Christos Pierrakeas A Semi-Supervised Regression Algorithm for Grade Prediction of Students in Distance Learning Courses. 1940001:1-1940001:19 2019 28 Int. J. Artif. Intell. Tools 4 https://doi.org/10.1142/S0218213019400013 https://www.wikidata.org/entity/Q66818334 db/journals/ijait/ijait28.html#KostopoulosKFKP19
Stamatios-Aggelos N. Alexandropoulos Sotiris B. Kotsiantis Michael N. Vrahatis Data preprocessing in predictive data mining. e1 2019 34 Knowl. Eng. Rev. https://doi.org/10.1017/S026988891800036X https://www.wikidata.org/entity/Q66802010 db/journals/ker/ker34.html#Alexandropoulos19
Nikos Fazakis Stamatis Karlos Sotiris Kotsiantis Kyriakos N. Sgarbas A multi-scheme semi-supervised regression approach. 758-765 2019 125 Pattern Recognit. Lett. https://doi.org/10.1016/j.patrec.2019.07.022 https://www.wikidata.org/entity/Q71953275 db/journals/prl/prl125.html#FazakisKKS19
Georgios Kostopoulos Stamatis Karlos Sotiris Kotsiantis Multiview Learning for Early Prognosis of Academic Performance: A Case Study. 212-224 2019 12 IEEE Trans. Learn. Technol. 2 https://doi.org/10.1109/TLT.2019.2911581 https://www.wikidata.org/entity/Q66808558 db/journals/tlt/tlt12.html#KostopoulosKK19
Stamatios-Aggelos N. Alexandropoulos Christos K. Aridas Sotiris B. Kotsiantis Michael N. Vrahatis A Deep Dense Neural Network for Bankruptcy Prediction. 435-444 2019 EANN https://doi.org/10.1007/978-3-030-20257-6_37 conf/eann/2019 db/conf/eann/eann2019.html#Alexandropoulos19 Stamatis Karlos Vasileios G. Kanas Nikos Fazakis Christos K. Aridas Sotiris Kotsiantis Investigating the Benefits of Exploiting Incremental Learners Under Active Learning Scheme. 37-49 2019 AIAI https://doi.org/10.1007/978-3-030-19823-7_3 conf/ifip12/2019aiai db/conf/ifip12/aiai2019.html#KarlosKFAK19 Stamatios-Aggelos N. Alexandropoulos Christos K. Aridas Sotiris B. Kotsiantis Michael N. Vrahatis Stacking Strong Ensembles of Classifiers. 545-556 2019 AIAI https://doi.org/10.1007/978-3-030-19823-7_46 conf/ifip12/2019aiai db/conf/ifip12/aiai2019.html#Alexandropoulos19 Nikos Fazakis Georgios Kostopoulos Stamatis Karlos Sotiris Kotsiantis Kyriakos N. Sgarbas Self-trained eXtreme Gradient Boosting Trees. 1-6 2019 IISA https://doi.org/10.1109/IISA.2019.8900737 conf/iisa/2019 db/conf/iisa/iisa2019.html#FazakisKKKS19 Stamatis Karlos Vasileios G. Kanas Christos K. Aridas Nikos Fazakis Sotiris Kotsiantis Combining Active Learning with Self-train algorithm for classification of multimodal problems. 1-8 2019 IISA https://doi.org/10.1109/IISA.2019.8900724 conf/iisa/2019 db/conf/iisa/iisa2019.html#KarlosKAFK19 Georgios Kostopoulos Nikos Fazakis Sotiris Kotsiantis Kyriakos N. Sgarbas Multi-objective Optimization of C4.5 Decision Tree for Predicting Student Academic Performance. 1-4 2019 IISA https://doi.org/10.1109/IISA.2019.8900771 conf/iisa/2019 db/conf/iisa/iisa2019.html#KostopoulosFKS19 Georgios S. Temponeras Stamatios-Aggelos N. Alexandropoulos Sotiris B. Kotsiantis Michael N. Vrahatis Financial Fraudulent Statements Detection through a Deep Dense Artificial Neural Network. 1-5 2019 IISA https://doi.org/10.1109/IISA.2019.8900741 conf/iisa/2019 db/conf/iisa/iisa2019.html#TemponerasAKV19 Dimitris G. Tsarmpopoulos Athanasia N. Papanikolaou Sotiris Kotsiantis Theodoula N. Grapsa George S. Androulakis Performance Evaluation and Comparison of Multi-objective optimization Algorithms. 1-6 2019 IISA https://doi.org/10.1109/IISA.2019.8900773 conf/iisa/2019 db/conf/iisa/iisa2019.html#TsarmpopoulosPK19 Aikaterini Karanikola Sotiris Kotsiantis A hybrid method for missing value imputation. 74-79 2019 PCI https://doi.org/10.1145/3368640.3368653 conf/pci/2019 db/conf/pci/pci2019.html#KaranikolaK19
George Kostopoulos Sotiris Kotsiantis Christos Pierrakeas Giannis Koutsonikos George A. Gravvanis Forecasting students' success in an open university. 26-43 2018 13 Int. J. Learn. Technol. 1 https://doi.org/10.1504/IJLT.2018.091630 db/journals/ijlt/ijlt13.html#KostopoulosKPKG18
Georgios Kostopoulos Ioannis E. Livieris Sotiris B. Kotsiantis Vassilis Tampakas CST-Voting: A semi-supervised ensemble method for classification problems. 99-109 2018 35 J. Intell. Fuzzy Syst. 1 https://doi.org/10.3233/JIFS-169571 db/journals/jifs/jifs35.html#KostopoulosLKT18
Georgios Kostopoulos Stamatis Karlos Sotiris Kotsiantis Omiros Ragos Semi-supervised regression: A recent review. 1483-1500 2018 35 J. Intell. Fuzzy Syst. 2 https://doi.org/10.3233/JIFS-169689 https://www.wikidata.org/entity/Q66809347 db/journals/jifs/jifs35.html#KostopoulosKKR18
Aikaterini Karanikola Stamatis Karlos Vangjel Kazllarof Eirini Kateri Sotiris Kotsiantis Active fuzzy rule induction. 1-8 2018 EAIS https://doi.org/10.1109/EAIS.2018.8397175 conf/eais/2018 db/conf/eais/eais2018.html#KaranikolaKKKK18 Stamatis Karlos Nikos Fazakis Konstantinos Kaleris Vasileios G. Kanas Sotiris Kotsiantis An incremental self-trained ensemble algorithm. 1-8 2018 EAIS https://doi.org/10.1109/EAIS.2018.8397180 conf/eais/2018 db/conf/eais/eais2018.html#KarlosFKKK18 Andreas F. Gkontzis Chris T. Panagiotakopoulos Sotiris Kotsiantis Vassilios S. Verykios Measuring Engagement to Assess Performance of Students in Distance Learning. 1-7 2018 IISA https://doi.org/10.1109/IISA.2018.8633607 https://doi.ieeecomputersociety.org/10.1109/IISA.2018.8633607 conf/iisa/2018 db/conf/iisa/iisa2018.html#GkontzisPKV18 Maria Tsiakmaki Georgios Kostopoulos Giannis Koutsonikos Christos Pierrakeas Sotiris Kotsiantis Omiros Ragos Predicting University Students' Grades Based on Previous Academic Achievements. 1-6 2018 IISA https://doi.org/10.1109/IISA.2018.8633618 https://doi.ieeecomputersociety.org/10.1109/IISA.2018.8633618 conf/iisa/2018 db/conf/iisa/iisa2018.html#TsiakmakiKKPKR18 Andreas F. Gkontzis Sotiris Kotsiantis Rozita Tsoni Vassilios S. Verykios An effective LA approach to predict student achievement. 76-81 2018 PCI https://doi.org/10.1145/3291533.3291551 conf/pci/2018 db/conf/pci/pci2018.html#GkontzisKTV18 Aikaterini Karanikola Stamatis Karlos Vangjel Kazllarof Sotiris Kotsiantis An incrementally updateable ensemble learner. 243-248 2018 PCI https://doi.org/10.1145/3291533.3291536 conf/pci/2018 db/conf/pci/pci2018.html#KaranikolaKKK18 Nikos Fazakis Stamatis Karlos Sotiris Kotsiantis Kyriakos N. Sgarbas A Semi-supervised regressor based on model trees. 6:1-6:7 2018 SETN https://doi.org/10.1145/3200947.3201033 conf/setn/2018 db/conf/setn/setn2018.html#FazakisKKS18 Stamatis Karlos Aikaterini Karanikola Vangjel Kazllarof Sotiris Kotsiantis Local weighted Averaged 2-Dependence Estimator. 28:1-28:4 2018 SETN https://doi.org/10.1145/3200947.3201047 conf/setn/2018 db/conf/setn/setn2018.html#KarlosKKK18 Stamatis Karlos Konstantinos Kaleris Nikos Fazakis Vasileios G. Kanas Sotiris Kotsiantis Optimized Active Learning Strategy for Audiovisual Speaker Recognition. 281-290 2018 SPECOM https://doi.org/10.1007/978-3-319-99579-3_30 conf/specom/2018 db/conf/specom/specom2018.html#KarlosKFKK18
Stamatis Karlos Nikos Fazakis Angeliki-Panagiota Panagopoulou Sotiris Kotsiantis Kyriakos N. Sgarbas Locally application of naive Bayes for self-training. 3-18 2017 8 Evol. Syst. 1 https://doi.org/10.1007/s12530-016-9159-3 db/journals/evs/evs8.html#KarlosFPKS17
Stamatis Karlos Nikos Fazakis Sotiris Kotsiantis Kyriakos N. Sgarbas Self-Trained Stacking Model for Semi-Supervised Learning. 1750001:1-1750001:21 2017 26 Int. J. Artif. Intell. Tools 2 https://doi.org/10.1142/S0218213017500014 https://www.wikidata.org/entity/Q67113552 db/journals/ijait/ijait26.html#KarlosFKS17
Sotiris Kotsiantis Nikolaos K. Tselios Michalis Xenos Students' evaluation of tutors in distance education: a quasi-longitudinal study. 26-41 2017 12 Int. J. Learn. Technol. 1 https://doi.org/10.1504/IJLT.2017.083995 db/journals/ijlt/ijlt12.html#KotsiantisTX17
Nikos Fazakis Stamatis Karlos Sotiris Kotsiantis Kyriakos N. Sgarbas Self-trained Rotation Forest for semi-supervised learning. 711-722 2017 32 J. Intell. Fuzzy Syst. 1 https://doi.org/10.3233/JIFS-152641 https://www.wikidata.org/entity/Q67172143 db/journals/jifs/jifs32.html#FazakisKKS17
Georgios Kostopoulos Stamatis Karlos Sotiris Kotsiantis Vassilis Tampakas Evaluating Active Learning Methods for Bankruptcy Prediction. 57-66 2017 BFAL https://doi.org/10.1007/978-3-319-67615-9_5 conf/bfal/2017 db/conf/bfal/bfal2017.html#KostopoulosKKT17 Georgios Kostopoulos Sotiris Kotsiantis Vassilios S. Verykios A Prognosis of Junior High School Students' Performance Based on Active Learning Methods. 67-76 2017 BFAL https://doi.org/10.1007/978-3-319-67615-9_6 conf/bfal/2017 db/conf/bfal/bfal2017.html#KostopoulosKV17 Georgios Kostopoulos Anastasia-Dimitra Lipitakis Sotiris Kotsiantis George A. Gravvanis Predicting Student Performance in Distance Higher Education Using Active Learning. 75-86 2017 EANN https://doi.org/10.1007/978-3-319-65172-9_7 conf/eann/2017 db/conf/eann/eann2017.html#KostopoulosLKG17 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. 111-121 2017 EANN https://doi.org/10.1007/978-3-319-65172-9_10 conf/eann/2017 db/conf/eann/eann2017.html#AridasAKV17 Stamatis Karlos Georgios Kostopoulos Sotiris Kotsiantis Vassilis Tampakas Using Active Learning Methods for Predicting Fraudulent Financial Statements. 351-362 2017 EANN https://doi.org/10.1007/978-3-319-65172-9_30 conf/eann/2017 db/conf/eann/eann2017.html#KarlosKKT17 Georgios Kostopoulos Sotiris Kotsiantis Omiros Ragos Theodoula N. Grapsa Early dropout prediction in distance higher education using active learning. 1-6 2017 IISA https://doi.org/10.1109/IISA.2017.8316424 conf/iisa/2017 db/conf/iisa/iisa2017.html#KostopoulosKRG17 Georgios Kostopoulos Ioannis E. Livieris Sotiris Kotsiantis Vassilis Tampakas Enhancing high school students' performance based on semi-supervised methods. 1-6 2017 IISA https://doi.org/10.1109/IISA.2017.8316425 conf/iisa/2017 db/conf/iisa/iisa2017.html#KostopoulosLKT17 Vangjel Kazllarof Stamatis Karlos Sotiris Kotsiantis Michalis Xenos Automated hand gesture recognition exploiting Active Learning methods. 3:1-3:6 2017 PCI https://doi.org/10.1145/3139367.3139414 conf/pci/2017 db/conf/pci/pci2017.html#KazllarofKKX17
Stamatis Karlos Nikos Fazakis Sotiris B. Kotsiantis Kyriakos N. Sgarbas A Semisupervised Cascade Classification Algorithm. 5919717:1-5919717:14 2016 2016 Appl. Comput. Intell. Soft Comput. https://doi.org/10.1155/2016/5919717 https://www.wikidata.org/entity/Q59121417 db/journals/acisc/acisc2016.html#KarlosFKS16
Nikos Fazakis Stamatis Karlos Sotiris B. Kotsiantis Kyriakos N. Sgarbas Self-Trained LMT for Semisupervised Learning. 3057481:1-3057481:13 2016 2016 Comput. Intell. Neurosci. https://doi.org/10.1155/2016/3057481 https://www.wikidata.org/entity/Q40029094 db/journals/cin/cin2016.html#FazakisKKS16
Christos K. Aridas Sotiris B. Kotsiantis Michael N. Vrahatis Increasing Diversity in Random Forests Using Naive Bayes. 75-86 2016 AIAI https://doi.org/10.1007/978-3-319-44944-9_7 conf/ifip12/2016aiai db/conf/ifip12/aiai2016.html#AridasKV16 Christos K. Aridas Sotiris B. Kotsiantis Michael N. Vrahatis Combining Prototype Selection with Local Boosting. 94-105 2016 AIAI https://doi.org/10.1007/978-3-319-44944-9_9 conf/ifip12/2016aiai db/conf/ifip12/aiai2016.html#AridasKV16a Nikos Fazakis Stamatis Karlos Sotiris Kotsiantis Kyriakos N. Sgarbas Self-labeled Hidden Naive Bayes algorithm for semi-supervised classification. 1-6 2016 IISA https://doi.org/10.1109/IISA.2016.7785414 conf/iisa/2016 db/conf/iisa/iisa2016.html#FazakisKKS16 Stamatis Karlos Sotiris Kotsiantis Nikos Fazakis Kyriakos N. Sgarbas Effectiveness of semi-supervised learning in bankruptcy prediction. 1-6 2016 IISA https://doi.org/10.1109/IISA.2016.7785435 conf/iisa/2016 db/conf/iisa/iisa2016.html#KarlosKFS16 Vangjel Kazllarof Stamatis Karlos Angeliki-Panagiota Panagopoulou Sotiris Kotsiantis Automated hand gesture recognition for educational applications. 20 2016 PCI https://doi.org/10.1145/3003733.3003746 conf/pci/2016 db/conf/pci/pci2016.html#KazllarofKPK16 Stamatis Karlos Nikos Fazakis Sotiris Kotsiantis Kyriakos N. Sgarbas Semi-supervised forecasting of fraudulent financial statements. 34 2016 PCI https://doi.org/10.1145/3003733.3003740 conf/pci/2016 db/conf/pci/pci2016.html#KarlosFKS16 Stamatis Karlos Nikos Fazakis Katerina Karanikola Sotiris B. Kotsiantis Kyriakos N. Sgarbas Speech Recognition Combining MFCCs and Image Features. 651-658 2016 SPECOM https://doi.org/10.1007/978-3-319-43958-7_79 conf/specom/2016 db/conf/specom/specom2016.html#KarlosFKKS16 Stamatis Karlos Nikos Fazakis Sotiris B. Kotsiantis Kyriakos N. Sgarbas Self-Train LogitBoost for Semi-supervised Learning. 139-148 2015 EANN https://doi.org/10.1007/978-3-319-23983-5_14 conf/eann/2015c db/conf/eann/eann2015c.html#KarlosFKS15 Anastasia-Dimitra Lipitakis Gerasimos S. Antzoulatos Sotiris Kotsiantis Michael N. Vrahatis Integrating global and local boosting. 1-6 2015 IISA https://doi.org/10.1109/IISA.2015.7388123 conf/iisa/2015 db/conf/iisa/iisa2015.html#LipitakisAKV15 Anastasia-Dimitra Lipitakis Sotiris Kotsiantis Combining ensembles algorithms of symbolic learners. 1-6 2015 IISA https://doi.org/10.1109/IISA.2015.7388118 conf/iisa/2015 db/conf/iisa/iisa2015.html#LipitakisK15 Georgios Kostopoulos Sotiris B. Kotsiantis Panagiotis E. Pintelas Predicting Student Performance in Distance Higher Education Using Semi-supervised Techniques. 259-270 2015 MEDI https://doi.org/10.1007/978-3-319-23781-7_21 conf/medi/2015 db/conf/medi/medi2015.html#KostopoulosKP15 Georgios Kostopoulos Sotiris B. Kotsiantis Panagiotis E. Pintelas Estimating student dropout in distance higher education using semi-supervised techniques. 38-43 2015 Panhellenic Conference on Informatics https://doi.org/10.1145/2801948.2802013 conf/pci/2015 db/conf/pci/pci2015.html#KostopoulosKP15 Christos K. Aridas Sotiris B. Kotsiantis Combining random forest and support vector machines for semi-supervised learning. 123-128 2015 Panhellenic Conference on Informatics https://doi.org/10.1145/2801948.2802011 conf/pci/2015 db/conf/pci/pci2015.html#AridasK15 Nikos Fazakis Stamatis Karlos Sotiris B. Kotsiantis Kyriakos N. Sgarbas Speaker Identification Using Semi-supervised Learning. 389-396 2015 SPECOM https://doi.org/10.1007/978-3-319-23132-7_48 conf/specom/2015 db/conf/specom/specom2015.html#FazakisKKS15
Sotiris B. Kotsiantis Integrating global and local application of naive bayes classifier. 300-307 2014 11 Int. Arab J. Inf. Technol. 3 http://iajit.org/index.php?option=com_content&task=blogcategory&id=92&Itemid=353 db/journals/iajit/iajit11.html#Kotsiantis14
Sotiris B. Kotsiantis A hybrid decision tree classifier. 327-336 2014 26 J. Intell. Fuzzy Syst. 1 https://doi.org/10.3233/IFS-120741 db/journals/jifs/jifs26.html#Kotsiantis14
Sotiris B. Kotsiantis Integrating global and local application of random subspace ensemble. 731-739 2014 26 J. Intell. Fuzzy Syst. 2 https://doi.org/10.3233/IFS-120763 db/journals/jifs/jifs26.html#Kotsiantis14a
Sotiris B. Kotsiantis Bagging and boosting variants for handling classifications problems: a survey. 78-100 2014 29 Knowl. Eng. Rev. 1 https://doi.org/10.1017/S0269888913000313 db/journals/ker/ker29.html#Kotsiantis14
Anastasia-Dimitra Lipitakis Sotirios Kotsiantis A hybrid Machine Learning methodology for imbalanced datasets. 252-257 2014 IISA https://doi.org/10.1109/IISA.2014.6878762 conf/iisa/2014 db/conf/iisa/iisa2014.html#LipitakisK14
Sotiris B. Kotsiantis Decision trees: a recent overview. 261-283 2013 39 Artif. Intell. Rev. 4 https://doi.org/10.1007/s10462-011-9272-4 db/journals/air/air39.html#Kotsiantis13
Sotiris B. Kotsiantis Use of machine learning techniques for educational proposes: a decision support system for forecasting students' grades. 331-344 2012 37 Artif. Intell. Rev. 4 https://doi.org/10.1007/s10462-011-9234-x db/journals/air/air37.html#Kotsiantis12
Sotiris B. Kotsiantis Integrating Global and Local Voting of Classifiers. 398-409 2012 43 Cybern. Syst. 5 https://doi.org/10.1080/01969722.2012.688684 db/journals/cas/cas43.html#Kotsiantis12
Dimitris Kanellopoulos Sotiris Kotsiantis Evaluating and recommending Greek newspapers' websites using clustering. 71-91 2012 46 Program 1 https://doi.org/10.1108/00330331211204575 db/journals/program/program46.html#KanellopoulosK12
Emmanuel Pappas Sotiris B. Kotsiantis Integrating Global and Local Application of Discriminative Multinomial Bayesian Classifier for Text Classification. 49-55 2012 ISI https://doi.org/10.1007/978-3-642-32063-7_6 conf/intelligent/2012 db/conf/intelligent/intelligent2012.html#PappasK12 Elias Zouboulidis Sotiris B. Kotsiantis Forecasting Fraudulent Financial Statements with Committee of Cost-Sensitive Decision Tree Classifiers. 57-64 2012 SETN https://doi.org/10.1007/978-3-642-30448-4_8 conf/setn/2012 db/conf/setn/setn2012.html#ZouboulidisK12 Despina Deligianni Sotiris B. Kotsiantis Forecasting Corporate Bankruptcy with an Ensemble of Classifiers. 65-72 2012 SETN https://doi.org/10.1007/978-3-642-30448-4_9 conf/setn/2012 db/conf/setn/setn2012.html#DeligianniK12 Elias Kamos Foteini Matthaiou Sotiris B. Kotsiantis Credit Rating Using a Hybrid Voting Ensemble. 165-173 2012 SETN https://doi.org/10.1007/978-3-642-30448-4_21 conf/setn/2012 db/conf/setn/setn2012.html#KamosMK12
Sotiris B. Kotsiantis Combining bagging, boosting, rotation forest and random subspace methods. 223-240 2011 35 Artif. Intell. Rev. 3 https://doi.org/10.1007/s10462-010-9192-8 db/journals/air/air35.html#Kotsiantis11
Sotiris B. Kotsiantis An incremental ensemble of classifiers. 249-266 2011 36 Artif. Intell. Rev. 4 https://doi.org/10.1007/s10462-011-9211-4 db/journals/air/air36.html#Kotsiantis11a
Sotiris B. Kotsiantis Cascade Generalization with Reweighting Data for Handling Imbalanced Problems. 1547-1559 2011 54 Comput. J. 9 https://doi.org/10.1093/comjnl/bxr016 db/journals/cj/cj54.html#Kotsiantis11
Sotiris B. Kotsiantis A random subspace method that uses different instead of similar models for regression and classification problems. 173-188 2011 3 Int. J. Inf. Decis. Sci. 2 https://doi.org/10.1504/IJIDS.2011.040422 db/journals/ijids/ijids3.html#Kotsiantis11
Dimitris Kanellopoulos Sotiris B. Kotsiantis Panayiotis E. Pintelas Intelligent Systems and Knowledge Management (Part II). 89-90 2011 11 J. Comput. Methods Sci. Eng. 3 https://doi.org/10.3233/JCM-2011-0366 db/journals/jcmse/jcmse11.html#KanellopoulosKP11
Sotiris B. Kotsiantis Dimitris Kanellopoulos Cascade generalisation for ordinal problems. 46-57 2010 2 Int. J. Artif. Intell. Soft Comput. 1/2 https://doi.org/10.1504/IJAISC.2010.032512 db/journals/ijaisc/ijaisc2.html#KotsiantisK10
Sotiris B. Kotsiantis Dimitris N. Kanellopoulos Bagging different instead of similar models for regression and classification problems. 20-28 2010 37 Int. J. Comput. Appl. Technol. 1 https://doi.org/10.1504/IJCAT.2010.030472 db/journals/ijcat/ijcat37.html#KotsiantisK10
Sotiris B. Kotsiantis Rotation-based model trees for classification. 22-37 2010 2 Int. J. Data Anal. Tech. Strateg. 1 https://doi.org/10.1504/IJDATS.2010.030009 db/journals/ijdats/ijdats2.html#Kotsiantis10
Sotiris B. Kotsiantis Local rotation-based ensemble. 147-160 2010 1 Int. J. Knowl. Eng. Data Min. 2 https://doi.org/10.1504/IJKEDM.2010.034841 db/journals/ijkedm/ijkedm1.html#Kotsiantis10
Sotiris B. Kotsiantis Dimitris Kanellopoulos Vasilis Tampakas Financial Application of Multi-Instance Learning: Two Greek Case Studies. 42-53 2010 5 J. Convergence Inf. Technol. 8 http://www.aicit.org/jcit/ppl/5-JCIT4-644093.pdf db/journals/jcit/jcit5.html#KotsiantisKT10
Sotiris B. Kotsiantis Kiriakos Patriarcheas Michalis Nik Xenos A combinational incremental ensemble of classifiers as a technique for predicting students' performance in distance education. 529-535 2010 23 Knowl. Based Syst. 6 https://doi.org/10.1016/j.knosys.2010.03.010 db/journals/kbs/kbs23.html#KotsiantisPX10
Sotiris B. Kotsiantis Locally application of random subspace with simple Bayesian classifier. 375-392 2009 1 Int. J. Data Min. Model. Manag. 4 https://doi.org/10.1504/IJDMMM.2009.029032 db/journals/ijdmmm/ijdmmm1.html#Kotsiantis09
Sotiris B. Kotsiantis Panayiotis E. Pintelas Selective costing ensemble for handling imbalanced data sets. 123-133 2009 6 Int. J. Hybrid Intell. Syst. 3 https://doi.org/10.3233/HIS-2009-0084 db/journals/ijhis/ijhis6.html#KotsiantisP09
Sotiris B. Kotsiantis Educational data mining: a case study for predicting dropout-prone students. 101-111 2009 1 Int. J. Knowl. Eng. Soft Data Paradigms 2 https://doi.org/10.1504/IJKESDP.2009.022718 db/journals/ijkesdp/ijkesdp1.html#Kotsiantis09
Sotiris B. Kotsiantis Locally application of cascade generalization for classification problems. 239-246 2008 2 Intell. Decis. Technol. 4 http://content.iospress.com/articles/intelligent-decision-technologies/idt00041 db/journals/idt/idt2.html#Kotsiantis08
Sotiris B. Kotsiantis Local reweight wrapper for the problem of imbalance. 25-38 2008 1 Int. J. Artif. Intell. Soft Comput. 1 https://doi.org/10.1504/IJAISC.2008.021262 db/journals/ijaisc/ijaisc1.html#Kotsiantis08
Sotiris B. Kotsiantis Handling imbalanced data sets with a modification of Decorate algorithm. 91-98 2008 33 Int. J. Comput. Appl. Technol. 2/3 https://doi.org/10.1504/IJCAT.2008.021931 db/journals/ijcat/ijcat33.html#Kotsiantis08
Sotiris B. Kotsiantis Dimitris Kanellopoulos Applying Machine Learning Techniques for Environmental Reporting. 217-223 2008 NCM (1) https://doi.org/10.1109/NCM.2008.119 https://doi.ieeecomputersociety.org/10.1109/NCM.2008.119 conf/ncm/2008-1 db/conf/ncm/ncm2008-1.html#KotsiantisK08 Sotiris B. Kotsiantis Local Grading of Learners. 209-213 2008 Panhellenic Conference on Informatics https://doi.org/10.1109/PCI.2008.16 https://doi.ieeecomputersociety.org/10.1109/PCI.2008.16 conf/pci/2008 db/conf/pci/pci2008.html#Kotsiantis08 Sotiris B. Kotsiantis Stacking Cost Sensitive Models. 217-221 2008 Panhellenic Conference on Informatics https://doi.org/10.1109/PCI.2008.15 https://doi.ieeecomputersociety.org/10.1109/PCI.2008.15 conf/pci/2008 db/conf/pci/pci2008.html#Kotsiantis08a
Sotiris B. Kotsiantis Credit risk analysis using a hybrid data mining model. 345-356 2007 2 Int. J. Intell. Syst. Technol. Appl. 4 https://doi.org/10.1504/IJISTA.2007.014030 db/journals/ijista/ijista2.html#Kotsiantis07
Sotiris B. Kotsiantis Supervised Machine Learning: A Review of Classification Techniques. 249-268 2007 31 Informatica (Slovenia) 3 http://www.informatica.si/index.php/informatica/article/view/148 db/journals/informaticaSI/informaticaSI31.html#Kotsiantis07
Sotiris B. Kotsiantis Dimitris Tzelepis Euaggelos Koumanakos Vasilis Tampakas Selective costing voting for bankruptcy prediction. 115-127 2007 11 Int. J. Knowl. Based Intell. Eng. Syst. 2 https://doi.org/10.3233/KES-2007-11204 db/journals/kes/kes11.html#KotsiantisTKT07
Dimitris Kanellopoulos Sotiris B. Kotsiantis Vasilis Tampakas Towards an ontology-based system for intelligent prediction of firms with fraudulent financial statements. 1300-1307 2007 ETFA https://doi.org/10.1109/EFTA.2007.4416931 conf/etfa/2007 db/conf/etfa/etfa2007.html#KanellopoulosKT07 D. Anyfantis M. Karagiannopoulos Sotiris B. Kotsiantis Panayiotis E. Pintelas Robustness of learning techniques in handling class noise in imbalanced datasets. 21-28 2007 AIAI https://doi.org/10.1007/978-0-387-74161-1_3 conf/ifip12/2007aiai db/conf/ifip12/aiai2007.html#AnyfantisKKP07 M. Karagiannopoulos D. Anyfantis Sotiris B. Kotsiantis Panayiotis E. Pintelas A Wrapper for Reweighting Training Instances for Handling Imbalanced Data Sets. 29-36 2007 AIAI https://doi.org/10.1007/978-0-387-74161-1_4 conf/ifip12/2007aiai db/conf/ifip12/aiai2007.html#KaragiannopoulosAKP07 Sotiris B. Kotsiantis Dimitris Kanellopoulos Combining Bagging, Boosting and Dagging for Classification Problems. 493-500 2007 conf/kes/2007-2 KES (2) https://doi.org/10.1007/978-3-540-74827-4_62 db/conf/kes/kes2007-2.html#KotsiantiK07 Sotiris B. Kotsiantis Supervised Machine Learning: A Review of Classification Techniques. 3-24 2007 Emerging Artificial Intelligence Applications in Computer Engineering series/faia/2007-160 db/series/faia/faia160.html#Kotsiantis07 http://www.booksonline.iospress.nl/Content/View.aspx?piid=6950
Sotiris B. Kotsiantis Ioannis D. Zaharakis Panayiotis E. Pintelas Machine learning: a review of classification and combining techniques. 159-190 2006 26 Artif. Intell. Rev. 3 https://doi.org/10.1007/s10462-007-9052-3 https://www.wikidata.org/entity/Q56483990 db/journals/air/air26.html#KotsiantisZP06
Sotiris B. Kotsiantis Local averaging of heterogeneous regression models. 99-107 2006 3 Int. J. Hybrid Intell. Syst. 2 http://content.iospress.com/articles/international-journal-of-hybrid-intelligent-systems/his00025 db/journals/ijhis/ijhis3.html#Kotsiantis06
Sotiris B. Kotsiantis Dimitris Kanellopoulos Panayiotis E. Pintelas Local Boosting of Decision Stumps for Regression and Classification Problems. 30-37 2006 1 J. Comput. 4 http://www.jcomputers.us/index.php?m=content&c=index&a=show&catid=91&id=1180 https://doi.org/10.4304/jcp.1.4.30-37 db/journals/jcp/jcp1.html#KotsiantisKP06
Dimitris Kanellopoulos Sotiris B. Kotsiantis Panayiotis E. Pintelas Ontology-based Learning Applications: A Development Methodology. 27-32 2006 conf/iastedSE/2006 IASTED Conf. on Software Engineering db/conf/iastedSE/se2006.html#KanellopoulosKP06 Sotiris B. Kotsiantis Euaggelos Koumanakos Dimitris Tzelepis Vasilis Tampakas Financial Application of Neural Networks: Two Case Studies in Greece. 672-681 2006 conf/icann/2006-2 ICANN (2) https://doi.org/10.1007/11840930_70 db/conf/icann/icann2006-2.html#KotsiantisKTT06 Sotiris B. Kotsiantis Local Ordinal Classification. 1-8 2006 conf/ifip12/2006aiai AIAI https://doi.org/10.1007/0-387-34224-9_1 db/conf/ifip12/aiai2006.html#Kotsiantis06 Sotiris B. Kotsiantis Dimitris Kanellopoulos Ioannis D. Zaharakis Bagged Averaging of Regression Models. 53-60 2006 conf/ifip12/2006aiai AIAI https://doi.org/10.1007/0-387-34224-9_7 db/conf/ifip12/aiai2006.html#KotsiantisKZ06 Sotiris B. Kotsiantis Dimitris Kanellopoulos Panayiotis E. Pintelas Local Additive Regression of Decision Stumps. 148-157 2006 conf/setn/2006 SETN https://doi.org/10.1007/11752912_17 db/conf/setn/setn2006.html#KotsiantisKP06 Sotiris B. Kotsiantis Euaggelos Koumanakos Dimitris Tzelepis Vasilis Tampakas Predicting Fraudulent Financial Statements with Machine Learning Techniques. 538-542 2006 conf/setn/2006 SETN https://doi.org/10.1007/11752912_63 db/conf/setn/setn2006.html#KotsiantisKTT06
Sotiris B. Kotsiantis Panayiotis E. Pintelas Logitboost of Simple Bayesian Classifier. 53-60 2005 29 Informatica (Slovenia) 1 http://www.informatica.si/index.php/informatica/article/view/17 db/journals/informaticaSI/informaticaSI29.html#KotsiantisP05
Sotiris B. Kotsiantis Panayiotis E. Pintelas Local voting of weak classifiers. 239-248 2005 9 Int. J. Knowl. Based Intell. Eng. Syst. 3 https://doi.org/10.3233/KES-2005-9308 db/journals/kes/kes9.html#KotsiantisP05
Sotiris B. Kotsiantis Panayiotis E. Pintelas Predicting Students' Marks in Hellenic Open University. 664-668 2005 conf/icalt/2005 ICALT https://doi.org/10.1109/ICALT.2005.223 https://doi.ieeecomputersociety.org/10.1109/ICALT.2005.223 db/conf/icalt/icalt2005.html#KotsiantisP05 Sotiris B. Kotsiantis George E. Tsekouras Panayiotis E. Pintelas Local Bagging of Decision Stumps. 406-411 2005 conf/ieaaie/2005 IEA/AIE https://doi.org/10.1007/11504894_57 db/conf/ieaaie/ieaaie2005.html#KotsiantisTP05 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. 705-708 2005 conf/ieaaie/2005 IEA/AIE https://doi.org/10.1007/11504894_97 db/conf/ieaaie/ieaaie2005.html#TsekourasPKKP05 Sotiris B. Kotsiantis George E. Tsekouras C. Raptis Panayiotis E. Pintelas Modeling the Organoleptic Properties of Matured Wine Distillates. 667-673 2005 conf/mldm/2005 MLDM https://doi.org/10.1007/11510888_66 db/conf/mldm/mldm2005.html#KotsiantisTRP05 Sotiris B. Kotsiantis George E. Tsekouras Panayiotis E. Pintelas Bagging Random Trees for Estimation of Tissue Softness. 674-681 2005 conf/mldm/2005 MLDM https://doi.org/10.1007/11510888_67 db/conf/mldm/mldm2005.html#KotsiantisTP05 Sotiris B. Kotsiantis George E. Tsekouras Panayiotis E. Pintelas Bagging Model Trees for Classification Problems. 328-337 2005 conf/pci/2005 Panhellenic Conference on Informatics https://doi.org/10.1007/11573036_31 https://www.wikidata.org/entity/Q62356815 db/conf/pci/pci2005.html#KotsiantisTP05
Sotiris B. Kotsiantis Christos Pierrakeas Panayiotis E. Pintelas Predicting Students' Performance In Distance Learning Using Machine Learning Techniques. 411-426 2004 18 Appl. Artif. Intell. 5 https://doi.org/10.1080/08839510490442058 https://www.wikidata.org/entity/Q58242749 db/journals/aai/aai18.html#KotsiantisPP04
Sotiris B. Kotsiantis Panayiotis E. Pintelas A decision support prototype tool for predicting student performance in an ODL environment. 253-264 2004 1 Interact. Technol. Smart Educ. 4 https://doi.org/10.1108/17415650480000027 db/journals/itse/itse1.html#KotsiantisP04
Sotiris B. Kotsiantis Panayiotis E. Pintelas Bagged Voting Ensembles. 168-177 https://doi.org/10.1007/978-3-540-30106-6_17 2004 conf/aimsa/2004 AIMSA db/conf/aimsa/aimsa2004.html#KotsiantisP04 Sotiris B. Kotsiantis Panayiotis E. Pintelas Increasing the Classification Accuracy of Simple Bayesian Classifier. 198-207 https://doi.org/10.1007/978-3-540-30106-6_20 2004 conf/aimsa/2004 AIMSA db/conf/aimsa/aimsa2004.html#KotsiantisP04a Sotiris B. Kotsiantis Panayiotis E. Pintelas A Hybrid Decision Support Tool - Using Ensemble of Classifiers. 448-456 2004 conf/iceis/2004 ICEIS (2) db/conf/iceis/iceis2004-2.html#KotsiantisP04 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. 202-206 2004 conf/ijit/2004icci International Conference on Computational Intelligence db/conf/ijit/icci2004.html#TsekourasPKKP04 Sotiris B. Kotsiantis Panayiotis E. Pintelas An Online Ensemble of Classifiers. 59-68 2004 conf/pris/2004 PRIS db/conf/pris/pris2004.html#KotsiantisP04 Sotiris B. Kotsiantis Panayiotis E. Pintelas A Cost Sensitive Technique for Ordinal Classification Problems. 220-229 https://doi.org/10.1007/978-3-540-24674-9_24 2004 conf/setn/2004 SETN db/conf/setn/setn2004.html#KotsiantisP04 Sotiris B. Kotsiantis Christos Pierrakeas Panayiotis E. Pintelas Preventing Student Dropout in Distance Learning Using Machine Learning Techniques. 267-274 https://doi.org/10.1007/978-3-540-45226-3_37 2003 conf/kes/2003-2 KES db/conf/kes/kes2003-2.html#KotsiantisPP03 Anthi Achriani Nikolaos Alachiotis 0002Nikolaos S. Alachiotis Stamatios-Aggelos N. Alexandropoulos Dimosthenis Anagnostopoulos George S. Androulakis Gerasimos AntzoulatosGerasimos S. Antzoulatos D. Anyfantis Christos K. Aridas Stavros Athanassopoulos Spiros A. Borotis Gregory Davrazos Despina Deligianni Nikos Fazakis Feng Feng 0003 Georgios Feretzakis C. K. Filelis-PapadopoulosChristos K. Filelis-Papadopoulos Georgia Garani Konstantinos M. Giannoutakis Andreas F. Gkontzis Aris Gkoulalas-Divanis Theodoula N. Grapsa George A. Gravvanis Konstantinos Kaleris Dimitrios KallesDimitris Kalles Christos Kalloniatis Achilles Kameas Elias Kamos Vasileios G. Kanas Dimitris KanellopoulosDimitris N. Kanellopoulos M. Karagiannopoulos Katerina KaranikolaAikaterini Karanikola Stamatis Karlos Eirini Kateri Vangjel Kazllarof Alireza Khastan Georgios KostopoulosGeorge Kostopoulos Dimitris E. Koumadorakis Euaggelos Koumanakos Giannis Koutsonikos Konstantinos Lavidas Fotis Lazarinis Konstantinos Lazaros Charalampos M. Liapis Meletis Liaskos Jerry Chun-Wei Lin Pantelis Linardatos Anastasia-Dimitra Lipitakis Ioannis E. Livieris Foteini Matthaiou Ioannis Messinis Iosif Mporas Iliana Paliari Dragan Pamucar Christos T. PanagiotakopoulosChris T. Panagiotakopoulos Theodor Panagiotakopoulos Angeliki-Panagiota Panagopoulou Dionysios Papadatos Dimitris Papageorgiou Athanasia N. Papanikolaou Vasilis Papastefanopoulos Emmanuel Pappas Kiriakos Patriarcheas Evgenia Paxinou Christos Pierrakeas Emmanuel Pintelas Panayiotis E. PintelasPanagiotis E. Pintelas Omiros Ragos C. Raptis Evangelos Sakkopoulos Athanasios SalamanisAthanasios I. Salamanis Kyriakos N. Sgarbas Gautam Srivastava 0001 Panos K. Syriopoulos Vassilis TampakasVasilis Tampakas Georgios S. Temponeras Stefania Tomasiello Dimitris G. Tsarmpopoulos George E. Tsekouras Nikolaos K. Tselios Maria Tsiakmaki Rozita Tsoni Manolis Tzagarakis Dimitris Tzelepis Vassilios S. Verykios Aristidis G. Vrahatis Michael N. Vrahatis Michalis Nik XenosMichalis Xenos Ioannis D. Zaharakis Elias Zouboulidis