Frederic T. Stahl

According to our database1, Frederic T. Stahl authored at least 48 papers between 2005 and 2018.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Bibliography

2018
Real-time feature selection technique with concept drift detection using adaptive micro-clusters for data stream mining.
Knowl.-Based Syst., 2018

Building Adaptive Data Mining Models on Streaming Data in Real-Time, an Outlook on Challenges, Approaches and Ongoing Research.
Proceedings of the European Conference on Modelling and Simulation, 2018

2017
On expressiveness and uncertainty awareness in rule-based classification for data streams.
Neurocomputing, 2017

Scalable real-time classification of data streams with concept drift.
Future Generation Comp. Syst., 2017

Improving Modular Classification Rule Induction with G-Prism Using Dynamic Rule Term Boundaries.
Proceedings of the Artificial Intelligence XXXIV, 2017

2016
A rule dynamics approach to event detection in Twitter with its application to sports and politics.
Expert Syst. Appl., 2016

A Method of Rule Induction for Predicting and Describing Future Alarms in a Telecommunication Network.
Proceedings of the Research and Development in Intelligent Systems XXXIII, 2016

Towards Expressive Modular Rule Induction for Numerical Attributes.
Proceedings of the Research and Development in Intelligent Systems XXXIII, 2016

A Statistical Learning Method to Fast Generalised Rule Induction Directly from Raw Measurements.
Proceedings of the 15th IEEE International Conference on Machine Learning and Applications, 2016

Towards Online Concept Drift Detection with Feature Selection for Data Stream Classification.
Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

2015
A Scalable Expressive Ensemble Learning Using Random Prism: A MapReduce Approach.
Trans. Large-Scale Data- and Knowledge-Centered Systems, 2015

Towards cost-sensitive adaptation: When is it worth updating your predictive model?
Neurocomputing, 2015

Towards Expressive Rule Induction on IP Network Event Streams.
Proceedings of the Research and Development in Intelligent Systems XXXII, 2015

Fast Adaptive Real-Time Classification for Data Streams with Concept Drift.
Proceedings of the Internet and Distributed Computing Systems, 2015

Optimisation Techniques for Parallel K-Means on MapReduce.
Proceedings of the Internet and Distributed Computing Systems, 2015

2014
Data stream mining in ubiquitous environments: state-of-the-art and current directions.
Wiley Interdiscip. Rev. Data Min. Knowl. Discov., 2014

A Survey of Data Mining Techniques for Social Media Analysis.
JDMDH, 2014

Random Prism: a noise-tolerant alternative to Random Forests.
Expert Systems, 2014

Towards a Parallel Computationally Efficient Approach to Scaling Up Data Stream Classification.
Proceedings of the Research and Development in Intelligent Systems XXXI, 2014

Computationally Efficient Rule-Based Classification for Continuous Streaming Data.
Proceedings of the Research and Development in Intelligent Systems XXXI, 2014

Extraction of Unexpected Rules from Twitter Hashtags and its Application to Sport Events.
Proceedings of the 13th International Conference on Machine Learning and Applications, 2014

Categorization and Construction of Rule Based Systems.
Proceedings of the Engineering Applications of Neural Networks, 2014

2013
An overview of interactive visual data mining techniques for knowledge discovery.
Wiley Interdiscip. Rev. Data Min. Knowl. Discov., 2013

Scaling up classification rule induction through parallel processing.
Knowledge Eng. Review, 2013

A Survey of Data Mining Techniques for Social Media Analysis.
CoRR, 2013

Efficient Interactive Budget Planning and Adjusting Under Financial Stress.
Proceedings of the Research and Development in Intelligent Systems XXX, 2013

Rule Type Identification Using TRCM for Trend Analysis in Twitter.
Proceedings of the Research and Development in Intelligent Systems XXX, 2013

TRCM: A Methodology for Temporal Analysis of Evolving Concepts in Twitter.
Proceedings of the Artificial Intelligence and Soft Computing, 2013

2012
An overview of the use of neural networks for data mining tasks.
Wiley Interdiscip. Rev. Data Min. Knowl. Discov., 2012

Homogeneous and Heterogeneous Distributed Classification for Pocket Data Mining.
Trans. Large-Scale Data- and Knowledge-Centered Systems, 2012

Computationally efficient induction of classification rules with the PMCRI and J-PMCRI frameworks.
Knowl.-Based Syst., 2012

Jmax-pruning: A facility for the information theoretic pruning of modular classification rules.
Knowl.-Based Syst., 2012

Parallel Random Prism: A Computationally Efficient Ensemble Learner for Classification.
Proceedings of the Research and Development in Intelligent Systems XXIX, 2012

eRules: A Modular Adaptive Classification Rule Learning Algorithm for Data Streams.
Proceedings of the Research and Development in Intelligent Systems XXIX, 2012

2011
Random Prism: An Alternative to Random Forests.
Proceedings of the Research and Development in Intelligent Systems XXVIII, 2011

Distributed Classification for Pocket Data Mining.
Proceedings of the Foundations of Intelligent Systems - 19th International Symposium, 2011

Distributed hoeffding trees for pocket data mining.
Proceedings of the 2011 International Conference on High Performance Computing & Simulation, 2011

2010
P-found: Grid-enabling distributed repositories of protein folding and unfolding simulations for data mining.
Future Generation Comp. Syst., 2010

Induction of Modular Classification Rules: Using Jmax-pruning.
Proceedings of the Research and Development in Intelligent Systems XXVII, 2010

J-PMCRI: A Methodology for Inducing Pre-pruned Modular Classification Rules.
Proceedings of the Artificial Intelligence in Theory and Practice III, 2010

Pocket Data Mining: Towards Collaborative Data Mining in Mobile Computing Environments.
Proceedings of the 22nd IEEE International Conference on Tools with Artificial Intelligence, 2010

2009
Parallel rule induction.
PhD thesis, 2009

Parallel Rule Induction with Information Theoretic Pre-Pruning.
Proceedings of the Research and Development in Intelligent Systems XXVI, 2009

PMCRI: A Parallel Modular Classification Rule Induction Framework.
Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2009

2008
P-Prism: A Computationally Efficient Approach to Scaling up Classification Rule Induction.
Proceedings of the Artificial Intelligence in Theory and Practice II, 2008

Grid Computing Solutions for Distributed Repositories of Protein Folding and Unfolding Simulations.
Proceedings of the Computational Science, 2008

2007
Towards a Computationally Efficient Approach to Modular Classification Rule Induction.
Proceedings of the Research and Development in Intelligent Systems XXIV, 2007

2005
Grid warehousing of molecular dynamics protein unfolding data.
Proceedings of the 5th International Symposium on Cluster Computing and the Grid (CCGrid 2005), 2005


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