Frederic T. Stahl

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 31

Top Topics

Numerical Attributes

Ensemble Classification

Top Venues

Publications

Christoph Tholen, Lars Nolle, Jochen Wollschlaeger, Frederic T. Stahl
Model Generalisation For Predicting The Amount Of Photosynthetically Available Radiation In The Water Column From Freefall Profiler Observations. ECMS (2024)
Daniel Lukats, Frederic T. Stahl
On Reproducible Implementations in Unsupervised Concept Drift Detection Algorithms Research. SGAI Conf. (2023)
Lars Nolle, Frederic T. Stahl, Tarek A. El-Mihoub
On Explanations for Hybrid Artificial Intelligence. SGAI Conf. (2023)
Manal Almutairi, Frederic T. Stahl, Max Bramer
CRC: Consolidated Rules Construction for Expressive Ensemble Classification. SGAI Conf. (2022)
Martin M. Kumm, Lars Nolle, Frederic T. Stahl, Ahlem Jemai, Oliver Zielinski
On an Artificial Neural Network Approach for Predicting Photosynthetically Active Radiation in the Water Column. SGAI Conf. (2022)
Frederic T. Stahl, Lars Nolle, Ahlem Jemai, Oliver Zielinski
A Model For Predicting The Amount Of Photosynthetically Available Radiation From BGC-ARGO Float Observations In The Water Column. ECMS (2022)
Mobin M. Idrees, Frederic T. Stahl, Atta Badii
Adaptive Learning With Extreme Verification Latency in Non-Stationary Environments. IEEE Access 10 (2022)
Ahmed Abadulla Ashlam, Atta Badii, Frederic T. Stahl
Multi-Phase Algorithmic Framework to Prevent SQL Injection Attacks using Improved Machine learning and Deep learning to Enhance Database security in Real-time. SIN (2022)
Tarek A. El-Mihoub, Lars Nolle, Frederic T. Stahl
Explainable Boosting Machines for Network Intrusion Detection with Features Reduction. SGAI Conf. (2022)
Saif Alzubi, Frederic T. Stahl, Mohamed Medhat Gaber
Towards Intrusion Detection Of Previously Unknown Network Attacks. ECMS (2021)
Frederic T. Stahl, Thien Le, Atta Badii, Mohamed Medhat Gaber
A Frequent Pattern Conjunction Heuristic for Rule Generation in Data Streams. Inf. 12 (1) (2021)
Frederic T. Stahl, Oliver Ferdinand, Lars Nolle, Alexandra Pehlken, Oliver Zielinski
AI Enabled Bio Waste Contamination-Scanner. SGAI Conf. (2021)
Manal Almutairi, Frederic T. Stahl, Max Bramer
ReG-Rules: An Explainable Rule-Based Ensemble Learner for Classification. IEEE Access 9 (2021)
Timothée Dubuc, Frederic T. Stahl, Etienne B. Roesch
Mapping the Big Data Landscape: Technologies, Platforms and Paradigms for Real-Time Analytics of Data Streams. IEEE Access 9 (2021)
Mobin M. Idrees, Leandro L. Minku, Frederic T. Stahl, Atta Badii
A heterogeneous online learning ensemble for non-stationary environments. Knowl. Based Syst. 188 (2020)
Chris Wrench, Frederic T. Stahl, Giuseppe Di Fatta, Vidhyalakshmi Karthikeyan, Detlef D. Nauck
A Rule Induction Approach to Forecasting Critical Alarms in a Telecommunication Network. ICDM Workshops (2019)
Manal Almutairi, Frederic T. Stahl, Max Bramer
A Rule-Based Classifier with Accurate and Fast Rule Term Induction for Continuous Attributes. ICMLA (2018)
Mahmood Hammoodi, Frederic T. Stahl, Atta Badii
Real-time feature selection technique with concept drift detection using adaptive micro-clusters for data stream mining. Knowl. Based Syst. 161 (2018)
Manal Almutairi, Frederic T. Stahl, Max Bramer
Improving Modular Classification Rule Induction with G-Prism Using Dynamic Rule Term Boundaries. SGAI Conf. (2017)
Mark Tennant, Frederic T. Stahl, Omer F. Rana, João Bártolo Gomes
Scalable real-time classification of data streams with concept drift. Future Gener. Comput. Syst. 75 (2017)
Thien Le, Frederic T. Stahl, Mohamed Medhat Gaber, João Bártolo Gomes, Giuseppe Di Fatta
On expressiveness and uncertainty awareness in rule-based classification for data streams. Neurocomputing 265 (2017)
Mahmood Hammoodi, Frederic T. Stahl, Mark Tennant
Towards Online Concept Drift Detection with Feature Selection for Data Stream Classification. ECAI (2016)
Chris Wrench, Frederic T. Stahl, Thien Le, Giuseppe Di Fatta, Vidhyalakshmi Karthikeyan, Detlef D. Nauck
A Method of Rule Induction for Predicting and Describing Future Alarms in a Telecommunication Network. SGAI Conf. (2016)
Manal Almutairi, Frederic T. Stahl, Mathew Jennings, Thien Le, Max Bramer
Towards Expressive Modular Rule Induction for Numerical Attributes. SGAI Conf. (2016)
Mariam Adedoyin-Olowe, Mohamed Medhat Gaber, Carlos J. Martín-Dancausa, Frederic T. Stahl, João Bártolo Gomes
A rule dynamics approach to event detection in Twitter with its application to sports and politics. Expert Syst. Appl. 55 (2016)
Thien Le, Frederic T. Stahl, Chris Wrench, Mohamed Medhat Gaber
A Statistical Learning Method to Fast Generalised Rule Induction Directly from Raw Measurements. ICMLA (2016)
Frederic T. Stahl, David May, Hugo Mills, Max Bramer, Mohamed Medhat Gaber
A Scalable Expressive Ensemble Learning Using Random Prism: A MapReduce Approach. Trans. Large Scale Data Knowl. Centered Syst. 20 (2015)
Indre Zliobaite, Marcin Budka, Frederic T. Stahl
Towards cost-sensitive adaptation: When is it worth updating your predictive model? Neurocomputing 150 (2015)
Sami Al Ghamdi, Giuseppe Di Fatta, Frederic T. Stahl
Optimisation Techniques for Parallel K-Means on MapReduce. IDCS (2015)
Mark Tennant, Frederic T. Stahl, João Bártolo Gomes
Fast Adaptive Real-Time Classification for Data Streams with Concept Drift. IDCS (2015)
Chris Wrench, Frederic T. Stahl, Giuseppe Di Fatta, Vidhyalakshmi Karthikeyan, Detlef D. Nauck
Towards Expressive Rule Induction on IP Network Event Streams. SGAI Conf. (2015)
Mariam Adedoyin-Olowe, Mohamed Medhat Gaber, Frederic T. Stahl
A Survey of Data Mining Techniques for Social Media Analysis. J. Data Min. Digit. Humanit. 2014 (2014)
Han Liu, Alexander E. Gegov, Frederic T. Stahl
Categorization and Construction of Rule Based Systems. EANN (2014)
Frederic T. Stahl, Max Bramer
Random Prism: a noise-tolerant alternative to Random Forests. Expert Syst. J. Knowl. Eng. 31 (5) (2014)
Mohamed Medhat Gaber, João Gama, Shonali Krishnaswamy, João Bártolo Gomes, Frederic T. Stahl
Data stream mining in ubiquitous environments: state-of-the-art and current directions. WIREs Data Mining Knowl. Discov. 4 (2) (2014)
Thien Le, Frederic T. Stahl, João Bártolo Gomes, Mohamed Medhat Gaber, Giuseppe Di Fatta
Computationally Efficient Rule-Based Classification for Continuous Streaming Data. SGAI Conf. (2014)
Mariam Adedoyin-Olowe, Mohamed Medhat Gaber, Carlos J. Martín-Dancausa, Frederic T. Stahl
Extraction of Unexpected Rules from Twitter Hashtags and its Application to Sport Events. ICMLA (2014)
Mark Tennant, Frederic T. Stahl, Giuseppe Di Fatta, João Bártolo Gomes
Towards a Parallel Computationally Efficient Approach to Scaling Up Data Stream Classification. SGAI Conf. (2014)
João Bártolo Gomes, Mariam Adedoyin-Olowe, Mohamed Medhat Gaber, Frederic T. Stahl
Rule Type Identification Using TRCM for Trend Analysis in Twitter. SGAI Conf. (2013)
Peter Rausch, Frederic T. Stahl, Michael Stumpf
Efficient Interactive Budget Planning and Adjusting Under Financial Stress. SGAI Conf. (2013)
Mariam Adedoyin-Olowe, Mohamed Medhat Gaber, Frederic T. Stahl
A Survey of Data Mining Techniques for Social Media Analysis. CoRR (2013)
Frederic T. Stahl, Max Bramer
Scaling up classification rule induction through parallel processing. Knowl. Eng. Rev. 28 (4) (2013)
Frederic T. Stahl, Bogdan Gabrys, Mohamed Medhat Gaber, Monika Berendsen
An overview of interactive visual data mining techniques for knowledge discovery. WIREs Data Mining Knowl. Discov. 3 (4) (2013)
Mariam Adedoyin-Olowe, Mohamed Medhat Gaber, Frederic T. Stahl
TRCM: A Methodology for Temporal Analysis of Evolving Concepts in Twitter. ICAISC (2) (2013)
Frederic T. Stahl, Ivan Jordanov
An overview of the use of neural networks for data mining tasks. WIREs Data Mining Knowl. Discov. 2 (3) (2012)
Frederic T. Stahl, Max Bramer
Computationally efficient induction of classification rules with the PMCRI and J-PMCRI frameworks. Knowl. Based Syst. 35 (2012)
Frederic T. Stahl, Mohamed Medhat Gaber, Paul Aldridge, David May, Han Liu, Max Bramer, Philip S. Yu
Homogeneous and Heterogeneous Distributed Classification for Pocket Data Mining. Trans. Large Scale Data Knowl. Centered Syst. 5 (2012)
Frederic T. Stahl, David May, Max Bramer
Parallel Random Prism: A Computationally Efficient Ensemble Learner for Classification. SGAI Conf. (2012)
Frederic T. Stahl, Max Bramer
Jmax-pruning: A facility for the information theoretic pruning of modular classification rules. Knowl. Based Syst. 29 (2012)
Frederic T. Stahl, Mohamed Medhat Gaber, Manuel Martin Salvador
eRules: A Modular Adaptive Classification Rule Learning Algorithm for Data Streams. SGAI Conf. (2012)
Frederic T. Stahl, Mohamed Medhat Gaber, Max Bramer, Philip S. Yu
Distributed hoeffding trees for pocket data mining. HPCS (2011)
Frederic T. Stahl, Max Bramer
Random Prism: An Alternative to Random Forests. SGAI Conf. (2011)
Frederic T. Stahl, Mohamed Medhat Gaber, Han Liu, Max Bramer, Philip S. Yu
Distributed Classification for Pocket Data Mining. ISMIS (2011)
Frederic T. Stahl, Mohamed Medhat Gaber, Max Bramer, Philip S. Yu
Pocket Data Mining: Towards Collaborative Data Mining in Mobile Computing Environments. ICTAI (2) (2010)
Frederic T. Stahl, Max Bramer, Mo Adda
J-PMCRI: A Methodology for Inducing Pre-pruned Modular Classification Rules. IFIP AI (2010)
Martin T. Swain, Cândida G. Silva, Nuno Loureiro-Ferreira, Vitaliy Ostropytskyy, João Brito, Olivier Riche, Frederic T. Stahl, Werner Dubitzky, Rui M. M. Brito
P-found: Grid-enabling distributed repositories of protein folding and unfolding simulations for data mining. Future Gener. Comput. Syst. 26 (3) (2010)
Frederic T. Stahl, Max Bramer
Induction of Modular Classification Rules: Using Jmax-pruning. SGAI Conf. (2010)
Frederic T. Stahl, Max A. Bramer, Mo Adda
PMCRI: A Parallel Modular Classification Rule Induction Framework. MLDM (2009)
Frederic T. Stahl, Max Bramer, Mo Adda
Parallel Rule Induction with Information Theoretic Pre-Pruning. SGAI Conf. (2009)
Frederic T. Stahl, Max A. Bramer, Mo Adda
P-Prism: A Computationally Efficient Approach to Scaling up Classification Rule Induction. IFIP AI (2008)
Martin T. Swain, Vitaliy Ostropytskyy, Cândida G. Silva, Frederic T. Stahl, Olivier Riche, Rui M. M. Brito, Werner Dubitzky
Grid Computing Solutions for Distributed Repositories of Protein Folding and Unfolding Simulations. ICCS (3) (2008)
Frederic T. Stahl, Max Bramer, Mo Adda
Parallel Induction of Modular Classification Rules. SGAI Conf. (2008)
Frederic T. Stahl, Max Bramer
Towards a Computationally Efficient Approach to Modular Classification Rule Induction. SGAI Conf. (2007)
Frederic T. Stahl, Daniel P. Berrar, Cândida G. Silva, R. J. Rodrigues, Rui M. M. Brito, Werner Dubitzky
Grid warehousing of molecular dynamics protein unfolding data. CCGRID (2005)