Eibe Frank

According to our database, Eibe Frank authored at least 128 papers between 1998 and 2024.

Collaborative distances:

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

2024

Hitting the target: stopping active learning at the cost-based optimum.

Zac Pullar-Strecker, Katharina Dost, Eibe Frank, Jörg Wicker

Mach. Learn., April, 2024

Feature extractor stacking for cross-domain few-shot learning.

Hongyu Wang, Eibe Frank, Bernhard Pfahringer, Michael Mayo, Geoff Holmes

Mach. Learn., January, 2024

Eliciting Informative Priors by Modeling Expert Decision Making.

Julia R. Falconer, Eibe Frank, Devon L. L. Polaschek, Chaitanya Joshi

Decis. Anal., 2024

Multiple Instance Verification.

Xin Xu, Eibe Frank, Geoffrey Holmes

CoRR, 2024

2023

teex: A toolbox for the evaluation of explanations.

Jesus Antonanzas, Yunzhe Jia, Eibe Frank, Albert Bifet, Bernhard Pfahringer

Neurocomputing, October, 2023

Large scale K-means clustering using GPUs.

Mi Li, Eibe Frank, Bernhard Pfahringer

Data Min. Knowl. Discov., 2023

Image Classification Using Class-Agnostic Object Detection.

Geoffrey Holmes, Eibe Frank, Dale Fletcher

Proceedings of the Artificial Intelligence Applications and Innovations, 2023

Self-trained Centroid Classifiers for Semi-supervised Cross-domain Few-shot Learning.

Hongyu Wang, Eibe Frank, Bernhard Pfahringer, Geoffrey Holmes

Proceedings of the Conference on Lifelong Learning Agents, 2023

2022

Bandwidth-Optimal Random Shuffling for GPUs.

Rory Mitchell, Daniel Stokes, Eibe Frank, Geoffrey Holmes

ACM Trans. Parallel Comput., 2022

GPUTreeShap: massively parallel exact calculation of SHAP scores for tree ensembles.

Rory Mitchell, Eibe Frank, Geoff Holmes

PeerJ Comput. Sci., 2022

Sampling Permutations for Shapley Value Estimation.

Rory Mitchell, Joshua Cooper, Eibe Frank, Geoffrey Holmes

J. Mach. Learn. Res., 2022

Methods for Eliciting Informative Prior Distributions: A Critical Review.

Julia R. Falconer, Eibe Frank, Devon L. L. Polaschek, Chaitanya Joshi

Decis. Anal., 2022

Cross-domain Few-shot Meta-learning Using Stacking.

Hongyu Wang, Eibe Frank, Bernhard Pfahringer, Michael Mayo, Geoffrey Holmes

CoRR, 2022

A simple but strong baseline for online continual learning: Repeated Augmented Rehearsal.

Yaqian Zhang, Bernhard Pfahringer, Eibe Frank, Albert Bifet, Nick Jin Sean Lim, Yunzhe Jia

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Efficiently correcting machine learning: considering the role of example ordering in human-in-the-loop training of image classification models.

Geoff Holmes, Eibe Frank, Dale Fletcher, Corey Sterling

Proceedings of the IUI 2022: 27th International Conference on Intelligent User Interfaces, Helsinki, Finland, March 22, 2022

Experiments in Cross-domain Few-shot Learning for Image Classification: Extended Abstract.

Hongyu Wang, Huon Fraser, Henry Gouk, Eibe Frank, Bernhard Pfahringer, Michael Mayo, Geoff Holmes

Proceedings of the ECML/PKDD Workshop on Meta-Knowledge Transfer, 2022

Better Self-training for Image Classification Through Self-supervision.

Attaullah Sahito, Eibe Frank, Bernhard Pfahringer

Proceedings of the AI 2021: Advances in Artificial Intelligence, 2022

2021

An Empirical Study of Moment Estimators for Quantile Approximation.

Rory Mitchell, Eibe Frank, Geoffrey Holmes

ACM Trans. Database Syst., 2021

Regularisation of neural networks by enforcing Lipschitz continuity.

Henry Gouk, Eibe Frank, Bernhard Pfahringer, Michael J. Cree

Mach. Learn., 2021

Classifier Chains: A Review and Perspectives.

Jesse Read, Bernhard Pfahringer, Geoff Holmes, Eibe Frank

J. Artif. Intell. Res., 2021

Deep learning in diabetic foot ulcers detection: A comprehensive evaluation.

Moi Hoon Yap, Ryo Hachiuma, Azadeh Alavi, Raphael Brüngel, Bill Cassidy, Manu Goyal, Hongtao Zhu, Johannes Rückert, Moshe Olshansky, Xiao Huang, Hideo Saito, Saeed Hassanpour, Christoph M. Friedrich, David B. Ascher, Anping Song, Hiroki Kajita, David Gillespie, Neil D. Reeves, Joseph M. Pappachan, Claire O'Shea, Eibe Frank

Comput. Biol. Medicine, 2021

Studying and Exploiting the Relationship Between Model Accuracy and Explanation Quality.

Yunzhe Jia, Eibe Frank, Bernhard Pfahringer, Albert Bifet, Nick Jin Sean Lim

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Perceptual improvements for Super-Resolution of Satellite Imagery.

Daniel Bull, Nick Jin Sean Lim, Eibe Frank

Proceedings of the 36th International Conference on Image and Vision Computing New Zealand, 2021

2020

GPUTreeShap: Fast Parallel Tree Interpretability.

Rory Mitchell, Eibe Frank, Geoffrey Holmes

CoRR, 2020

DFUC2020: Analysis Towards Diabetic Foot Ulcer Detection.

Bill Cassidy, Neil D. Reeves, Joseph Pappachan, David Gillespie, Claire O'Shea, Satyan Rajbhandari, Arun G. Maiya, Eibe Frank, Andrew Boulton, David G. Armstrong, Bijan Najafi, Justina Wu, Moi Hoon Yap

CoRR, 2020

Improving Naive Bayes for Regression with Optimized Artificial Surrogate Data.

Michael Mayo, Eibe Frank

Appl. Artif. Intell., 2020

Embedding Java Classes with code2vec: Improvements from Variable Obfuscation.

Rhys Compton, Eibe Frank, Panos Patros, Abigail M. Y. Koay

Proceedings of the MSR '20: 17th International Conference on Mining Software Repositories, 2020

Adaptive XGBoost for Evolving Data Streams.

Jacob Montiel, Rory Mitchell, Eibe Frank, Bernhard Pfahringer, Talel Abdessalem, Albert Bifet

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

A Comparison of Machine Learning Methods for Cross-Domain Few-Shot Learning.

Hongyu Wang, Henry Gouk, Eibe Frank, Bernhard Pfahringer, Michael Mayo

Proceedings of the AI 2020: Advances in Artificial Intelligence, 2020

Transfer of Pretrained Model Weights Substantially Improves Semi-supervised Image Classification.

Attaullah Sahito, Eibe Frank, Bernhard Pfahringer

Proceedings of the AI 2020: Advances in Artificial Intelligence, 2020

2019

WekaDeeplearning4j: A deep learning package for Weka based on Deeplearning4j.

Steven Lang, Felipe Bravo-Marquez, Christopher Beckham, Mark A. Hall, Eibe Frank

Knowl. Based Syst., 2019

AffectiveTweets: a Weka Package for Analyzing Affect in Tweets.

Felipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringer, Saif M. Mohammad

J. Mach. Learn. Res., 2019

Ensembles of Nested Dichotomies with Multiple Subset Evaluation.

Tim Leathart, Eibe Frank, Bernhard Pfahringer, Geoffrey Holmes

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

On Calibration of Nested Dichotomies.

Tim Leathart, Eibe Frank, Bernhard Pfahringer, Geoffrey Holmes

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

Semi-supervised Learning Using Siamese Networks.

Attaullah Sahito, Eibe Frank, Bernhard Pfahringer

Proceedings of the AI 2019: Advances in Artificial Intelligence, 2019

Stochastic Gradient Trees.

Henry Gouk, Bernhard Pfahringer, Eibe Frank

Proceedings of The 11th Asian Conference on Machine Learning, 2019

2018

Transferring sentiment knowledge between words and tweets.

Felipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringer

Web Intell., 2018

Online estimation of discrete, continuous, and conditional joint densities using classifier chains.

Michael Geilke, Andreas Karwath, Eibe Frank, Stefan Kramer

Data Min. Knowl. Discov., 2018

On the Calibration of Nested Dichotomies for Large Multiclass Tasks.

Tim Leathart, Eibe Frank, Bernhard Pfahringer, Geoffrey Holmes

CoRR, 2018

XGBoost: Scalable GPU Accelerated Learning.

Rory Mitchell, Andrey Adinets, Thejaswi Rao, Eibe Frank

CoRR, 2018

Good Vibrations: Artificial Ambience-Based Relay Attack Detection.

Iakovos Gurulian, Konstantinos Markantonakis, Eibe Frank, Raja Naeem Akram

Proceedings of the 17th IEEE International Conference On Trust, 2018

MaxGain: Regularisation of Neural Networks by Constraining Activation Magnitudes.

Henry Gouk, Bernhard Pfahringer, Eibe Frank, Michael J. Cree

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Hidden Features: Experiments with Feature Transfer for Fine-Grained Multi-Class and One-Class Image Categorization.

Varvara Vetrova, Sheldon Coup, Eibe Frank, Michael J. Cree

Proceedings of the 2018 International Conference on Image and Vision Computing New Zealand, 2018

2017

Accelerating the XGBoost algorithm using GPU computing.

Rory Mitchell, Eibe Frank

PeerJ Prepr., 2017

Improving Naive Bayes for Regression with Optimised Artificial Surrogate Data.

Michael Mayo, Eibe Frank

CoRR, 2017

On the Effectiveness of Ambient Sensing for Detecting NFC Relay Attacks.

Iakovos Gurulian, Carlton Shepherd, Eibe Frank, Konstantinos Markantonakis, Raja Naeem Akram, Keith Mayes

Proceedings of the 2017 IEEE Trustcom/BigDataSE/ICESS, Sydney, Australia, August 1-4, 2017, 2017

The Applicability of Ambient Sensors as Proximity Evidence for NFC Transactions.

Carlton Shepherd, Iakovos Gurulian, Eibe Frank, Konstantinos Markantonakis, Raja Naeem Akram, Emmanouil Panaousis, Keith Mayes

Proceedings of the 2017 IEEE Security and Privacy Workshops, 2017

Proximity Assurances Based on Natural and Artificial Ambient Environments.

Iakovos Gurulian, Konstantinos Markantonakis, Carlton Shepherd, Eibe Frank, Raja Naeem Akram

Proceedings of the Innovative Security Solutions for Information Technology and Communications, 2017

Learning Through Utility Optimization in Regression Tasks.

Paula Branco, Luís Torgo, Rita P. Ribeiro, Eibe Frank, Bernhard Pfahringer, Markus Michael Rau

Proceedings of the 2017 IEEE International Conference on Data Science and Advanced Analytics, 2017

Large-Scale Automatic Species Identification.

Jeff Mo, Eibe Frank, Varvara Vetrova

Proceedings of the AI 2017: Advances in Artificial Intelligence, 2017

Probability Calibration Trees.

Tim Leathart, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer

Proceedings of The 9th Asian Conference on Machine Learning, 2017

2016

Building a Twitter opinion lexicon from automatically-annotated tweets.

Felipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringer

Knowl. Based Syst., 2016

From Opinion Lexicons to Sentiment Classification of Tweets and Vice Versa: A Transfer Learning Approach.

Felipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringer

Proceedings of the 2016 IEEE/WIC/ACM International Conference on Web Intelligence, 2016

Determining Word-Emotion Associations from Tweets by Multi-label Classification.

Felipe Bravo-Marquez, Eibe Frank, Saif M. Mohammad, Bernhard Pfahringer

Proceedings of the 2016 IEEE/WIC/ACM International Conference on Web Intelligence, 2016

Building Ensembles of Adaptive Nested Dichotomies with Random-Pair Selection.

Tim Leathart, Bernhard Pfahringer, Eibe Frank

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Annotate-Sample-Average (ASA): A New Distant Supervision Approach for Twitter Sentiment Analysis.

Felipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringer

Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

Introducing Machine Learning Concepts with WEKA.

Tony C. Smith, Eibe Frank

Proceedings of the Statistical Genomics - Methods and Protocols, 2016

2015

From Unlabelled Tweets to Twitter-specific Opinion Words.

Felipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringer

Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2015

Alternating model trees.

Eibe Frank, Michael Mayo, Stefan Kramer

Proceedings of the 30th Annual ACM Symposium on Applied Computing, 2015

Positive, Negative, or Neutral: Learning an Expanded Opinion Lexicon from Emoticon-Annotated Tweets.

Felipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringer

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

2013

Online Estimation of Discrete Densities.

Michael Geilke, Eibe Frank, Andreas Karwath, Stefan Kramer

Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

Propositionalisation of Multi-instance Data Using Random Forests.

Eibe Frank, Bernhard Pfahringer

Proceedings of the AI 2013: Advances in Artificial Intelligence, 2013

2012

Ensembles of Restricted Hoeffding Trees.

Albert Bifet, Eibe Frank, Geoff Holmes, Bernhard Pfahringer

ACM Trans. Intell. Syst. Technol., 2012

Learning a concept-based document similarity measure.

Anna-Lan Huang, David N. Milne, Eibe Frank, Ian H. Witten

J. Assoc. Inf. Sci. Technol., 2012

2011

Classifier chains for multi-label classification.

Jesse Read, Bernhard Pfahringer, Geoff Holmes, Eibe Frank

Mach. Learn., 2011

Beyond Trees: Adopting MITI to Learn Rules and Ensemble Classifiers for Multi-Instance Data.

Luke Bjerring, Eibe Frank

Proceedings of the AI 2011: Advances in Artificial Intelligence, 2011

Data mining: practical machine learning tools and techniques, 3rd Edition.

Ian H. Witten, Eibe Frank, Mark A. Hall

Morgan Kaufmann, Elsevier, ISBN: 9780123748560, 2011

2010

Weka-A Machine Learning Workbench for Data Mining.

Eibe Frank, Mark A. Hall, Geoffrey Holmes, Richard Kirkby, Bernhard Pfahringer, Ian H. Witten, Len Trigg

Proceedings of the Data Mining and Knowledge Discovery Handbook, 2nd ed., 2010

A Study of Hierarchical and Flat Classification of Proteins.

Arthur Zimek, Fabian Buchwald, Eibe Frank, Stefan Kramer

IEEE ACM Trans. Comput. Biol. Bioinform., 2010

A review of multi-instance learning assumptions.

James R. Foulds, Eibe Frank

Knowl. Eng. Rev., 2010

WEKA - Experiences with a Java Open-Source Project.

Remco R. Bouckaert, Eibe Frank, Mark A. Hall, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, Ian H. Witten

J. Mach. Learn. Res., 2010

Accurate Ensembles for Data Streams: Combining Restricted Hoeffding Trees using Stacking.

Albert Bifet, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer

Proceedings of the 2nd Asian Conference on Machine Learning, 2010

Fast Perceptron Decision Tree Learning from Evolving Data Streams.

Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer, Eibe Frank

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2010

Speeding Up and Boosting Diverse Density Learning.

James R. Foulds, Eibe Frank

Proceedings of the Discovery Science - 13th International Conference, 2010

Sentiment Knowledge Discovery in Twitter Streaming Data.

Albert Bifet, Eibe Frank

Proceedings of the Discovery Science - 13th International Conference, 2010

Fast Conditional Density Estimation for Quantitative Structure-Activity Relationships.

Fabian Buchwald, Tobias Girschick, Eibe Frank, Stefan Kramer

Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

2009

The WEKA data mining software: an update.

Mark A. Hall, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, Ian H. Witten

SIGKDD Explor., 2009

Accuracy of machine learning models versus "hand crafted" expert systems - A credit scoring case study.

Arie Ben-David, Eibe Frank

Expert Syst. Appl., 2009

Clustering Documents Using a Wikipedia-Based Concept Representation.

Anna-Lan Huang, David N. Milne, Eibe Frank, Ian H. Witten

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2009

Analysing chromatographic data using data mining to monitor petroleum content in water.

Geoffrey Holmes, Dale Fletcher, Peter Reutemann, Eibe Frank

Proceedings of the Information Technologies in Environmental Engineering, 2009

Human-competitive tagging using automatic keyphrase extraction.

Olena Medelyan, Eibe Frank, Ian H. Witten

Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, 2009

Large-scale attribute selection using wrappers.

Martin Gütlein, Eibe Frank, Mark A. Hall, Andreas Karwath

Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, 2009

Conditional Density Estimation with Class Probability Estimators.

Eibe Frank, Remco R. Bouckaert

Proceedings of the Advances in Machine Learning, 2009

2008

One-Class Classification by Combining Density and Class Probability Estimation.

Kathryn Hempstalk, Eibe Frank, Ian H. Witten

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2008

Clustering Documents with Active Learning Using Wikipedia.

Anna-Lan Huang, David N. Milne, Eibe Frank, Ian H. Witten

Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

Combining Naive Bayes and Decision Tables.

Mark A. Hall, Eibe Frank

Proceedings of the Twenty-First International Florida Artificial Intelligence Research Society Conference, 2008

Discriminating Against New Classes: One-class versus Multi-class Classification.

Kathryn Hempstalk, Eibe Frank

Proceedings of the AI 2008: Advances in Artificial Intelligence, 2008

Additive Regression Applied to a Large-Scale Collaborative Filtering Problem.

Eibe Frank, Mark A. Hall

Proceedings of the AI 2008: Advances in Artificial Intelligence, 2008

Revisiting Multiple-Instance Learning Via Embedded Instance Selection.

James R. Foulds, Eibe Frank

Proceedings of the AI 2008: Advances in Artificial Intelligence, 2008

Data Mining - Know It All.

Soumen Chakrabarti, Earl Cox, Eibe Frank, Ralf Hartmut Güting, Jiawei Han, Xia Jiang, Micheline Kamber, Sam Lightstone, Thomas P. Nadeau, Richard E. Neapolitan, Dorian Pyle, Mamdouh Refaat, Markus Schneider, Toby J. Teorey, Ian H. Witten

Morgan Kaufmann, ISBN: 978-0-12-374629-0, 2008

2007

An Empirical Comparison of Exact Nearest Neighbour Algorithms.

Ashraf M. Kibriya, Eibe Frank

Proceedings of the Knowledge Discovery in Databases: PKDD 2007, 2007

2006

Naive Bayes for Text Classification with Unbalanced Classes.

Eibe Frank, Remco R. Bouckaert

Proceedings of the Knowledge Discovery in Databases: PKDD 2006, 2006

Improving on Bagging with Input Smearing.

Eibe Frank, Bernhard Pfahringer

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2006

2005

Logistic Model Trees.

Niels Landwehr, Mark A. Hall, Eibe Frank

Mach. Learn., 2005

Gene selection from microarray data for cancer classification - a machine learning approach.

Yu Wang, Igor V. Tetko, Mark A. Hall, Eibe Frank, Axel Facius, Klaus F. X. Mayer, Hans-Werner Mewes

Comput. Biol. Chem., 2005

Speeding Up Logistic Model Tree Induction.

Marc Sumner, Eibe Frank, Mark A. Hall

Proceedings of the Knowledge Discovery in Databases: PKDD 2005, 2005

Unsupervised Discretization Using Tree-Based Density Estimation.

Gabi Schmidberger, Eibe Frank

Proceedings of the Knowledge Discovery in Databases: PKDD 2005, 2005

Ensembles of Balanced Nested Dichotomies for Multi-class Problems.

Lin Dong, Eibe Frank, Stefan Kramer

Proceedings of the Knowledge Discovery in Databases: PKDD 2005, 2005

WEKA - A Machine Learning Workbench for Data Mining.

Eibe Frank, Mark A. Hall, Geoffrey Holmes, Richard Kirkby, Bernhard Pfahringer

Proceedings of the Data Mining and Knowledge Discovery Handbook., 2005

Data mining - practical machine learning tools and techniques, Second Edition.

Ian H. Witten, Eibe Frank

The Morgan Kaufmann series in data management systems, Morgan Kaufmann, ISBN: 978-0-12-088407-0, 2005

2004

Predicting Library of Congress classifications from Library of Congress subject headings.

Eibe Frank, Gordon W. Paynter

J. Assoc. Inf. Sci. Technol., 2004

Data mining in bioinformatics using Weka.

Eibe Frank, Mark A. Hall, Leonard E. Trigg, Geoffrey Holmes, Ian H. Witten

Bioinform., 2004

Logistic Regression and Boosting for Labeled Bags of Instances.

Xin Xu, Eibe Frank

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2004

Evaluating the Replicability of Significance Tests for Comparing Learning Algorithms.

Remco R. Bouckaert, Eibe Frank

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2004

Ensembles of nested dichotomies for multi-class problems.

Eibe Frank, Stefan Kramer

Proceedings of the Machine Learning, 2004

A Toolbox for Learning from Relational Data with Propositional and Multi-instance Learners.

Peter Reutemann, Bernhard Pfahringer, Eibe Frank

Proceedings of the AI 2004: Advances in Artificial Intelligence, 2004

Using Classification to Evaluate the Output of Confidence-Based Association Rule Mining.

Stefan Mutter, Mark A. Hall, Eibe Frank

Proceedings of the AI 2004: Advances in Artificial Intelligence, 2004

Multinomial Naive Bayes for Text Categorization Revisited.

Ashraf M. Kibriya, Eibe Frank, Bernhard Pfahringer, Geoffrey Holmes

Proceedings of the AI 2004: Advances in Artificial Intelligence, 2004

2003

Locally Weighted Naive Bayes.

Eibe Frank, Mark A. Hall, Bernhard Pfahringer

Proceedings of the UAI '03, 2003

Visualizing Class Probability Estimators.

Eibe Frank, Mark A. Hall

Proceedings of the Knowledge Discovery in Databases: PKDD 2003, 2003

A Two-Level Learning Method for Generalized Multi-instance Problems.

Nils Weidmann, Eibe Frank, Bernhard Pfahringer

Proceedings of the Machine Learning: ECML 2003, 2003

2002

Multiclass Alternating Decision Trees.

Geoffrey Holmes, Bernhard Pfahringer, Richard Kirkby, Eibe Frank, Mark A. Hall

Proceedings of the Machine Learning: ECML 2002, 2002

Racing Committees for Large Datasets.

Eibe Frank, Geoffrey Holmes, Richard Kirkby, Mark A. Hall

Proceedings of the Discovery Science, 5th International Conference, 2002

2001

Interactive machine learning: letting users build classifiers.

Malcolm Ware, Eibe Frank, Geoffrey Holmes, Mark A. Hall, Ian H. Witten

Int. J. Hum. Comput. Stud., 2001

Determining Progression in Glaucoma Using Visual Fields.

Andrew Turpin, Eibe Frank, Mark A. Hall, Ian H. Witten, Chris A. Johnson

Proceedings of the Knowledge Discovery and Data Mining, 2001

A Simple Approach to Ordinal Classification.

Eibe Frank, Mark A. Hall

Proceedings of the Machine Learning: EMCL 2001, 2001

2000

Naive Bayes for Regression (Technical Note).

Eibe Frank, Leonard E. Trigg, Geoffrey Holmes, Ian H. Witten

Mach. Learn., 2000

Bottom-Up Propositionalization.

Stefan Kramer, Eibe Frank

Proceedings of the Inductive Logic Programming, 10th International Conference, 2000

Text Categorization Using Compression Models.

Eibe Frank, Chang Chui, Ian H. Witten

Proceedings of the Data Compression Conference, 2000

1999

Improving browsing in digital libraries with keyphrase indexes.

Carl Gutwin, Gordon W. Paynter, Ian H. Witten, Craig G. Nevill-Manning, Eibe Frank

Decis. Support Syst., 1999

Domain-Specific Keyphrase Extraction.

Eibe Frank, Gordon W. Paynter, Ian H. Witten, Carl Gutwin, Craig G. Nevill-Manning

Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, 1999

Making Better Use of Global Discretization.

Eibe Frank, Ian H. Witten

Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27, 1999

KEA: Practical Automatic Keyphrase Extraction.

Ian H. Witten, Gordon W. Paynter, Eibe Frank, Carl Gutwin, Craig G. Nevill-Manning

Proceedings of the Fourth ACM conference on Digital Libraries, 1999

Generating Rule Sets from Model Trees.

Geoffrey Holmes, Mark A. Hall, Eibe Frank

Proceedings of the Advanced Topics in Artificial Intelligence, 1999

Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations

Ian H. Witten, Eibe Frank

Morgan Kaufmann, ISBN: 1-55860-552-5, 1999

1998

Using Model Trees for Classification.

Eibe Frank, Yong Wang, Stuart Inglis, Geoffrey Holmes, Ian H. Witten

Mach. Learn., 1998

Using a Permutation Test for Attribute Selection in Decision Trees.

Eibe Frank, Ian H. Witten

Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), 1998

Generating Accurate Rule Sets Without Global Optimization.

Eibe Frank, Ian H. Witten

Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), 1998