Eibe Frank - RankMe

160 papers A* 12A 4B 13C 5Misc 5Journal 73Unranked 41

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Policy Gradient with Adaptive Entropy Annealing for Continual Fine-Tuning. CoRR Yaqian Zhang, Bernhard Pfahringer, Eibe Frank, Albert Bifet
2026	J	`jnl`	Using Multi-Instance Learning to Identify Unique Polyps in Colon Capsule Endoscopy Images. CoRR Puneet Sharma, Kristian Dalsbø Hindberg, Eibe Frank, Benedicte Schelde-Olesen, Ulrik Deding
2025	J	`jnl`	A comparative study of four deep learning algorithms for predicting tree stem radius measured by dendrometer: A case study. Ecol. Informatics Guilherme Weigert Cassales, Serajis Salekin, Nick Jin Sean Lim, Dean F. Meason, Albert Bifet, Bernhard Pfahringer, Eibe Frank
2025	J	`jnl`	Experiments with Optimal Model Trees. CoRR Sabino Francesco Roselli, Eibe Frank
2025	J	`jnl`	Few-shot Classification as Multi-instance Verification: Effective Backbone-agnostic Transfer across Domains. CoRR Xin Xu, Eibe Frank, Geoff Holmes
2025	J	`jnl`	Multiple Instance Verification. J. Mach. Learn. Res. Xin Xu, Eibe Frank, Geoffrey Holmes
2025	J	`jnl`	Pruning Feature Extractor Stacking for Cross-domain Few-shot Learning. Trans. Mach. Learn. Res. Hongyu Wang, Eibe Frank, Bernhard Pfahringer, Geoff Holmes
2025	J	`jnl`	Rethinking Memory in Continual Learning: Beyond a Monolithic Store of the Past. Trans. Mach. Learn. Res. Yaqian Zhang, Bernhard Pfahringer, Eibe Frank, Albert Bifet
2025	J	`jnl`	Revisiting Deep Hybrid Models for Out-of-Distribution Detection. Trans. Mach. Learn. Res. Paul-Ruben Schlumbom, Eibe Frank
2025	J	`jnl`	Utilising Deep Learning to Elicit Expert Uncertainty. CoRR Julia R. Falconer, Eibe Frank, Devon L. L. Polaschek, Chaitanya Joshi
2024	J	`jnl`	Eliciting Informative Priors by Modeling Expert Decision Making. Decis. Anal. Julia R. Falconer, Eibe Frank, Devon L. L. Polaschek, Chaitanya Joshi
2024	J	`jnl`	Feature extractor stacking for cross-domain few-shot learning. Mach. Learn. Hongyu Wang, Eibe Frank, Bernhard Pfahringer, Michael Mayo, Geoff Holmes
2024	J	`jnl`	Hitting the target: stopping active learning at the cost-based optimum. Mach. Learn. Zac Pullar-Strecker, Katharina Dost, Eibe Frank, Jörg Wicker
2024	J	`jnl`	Multiple Instance Verification. CoRR Xin Xu, Eibe Frank, Geoffrey Holmes
2023	—	`conf`	Image Classification Using Class-Agnostic Object Detection. AIAI (1) Geoffrey Holmes, Eibe Frank, Dale Fletcher
2023	J	`jnl`	Large scale K-means clustering using GPUs. Data Min. Knowl. Discov. Mi Li, Eibe Frank, Bernhard Pfahringer
2023	—	`conf`	Self-trained Centroid Classifiers for Semi-supervised Cross-domain Few-shot Learning. CoLLAs Hongyu Wang, Eibe Frank, Bernhard Pfahringer, Geoffrey Holmes
2023	J	`jnl`	teex: A toolbox for the evaluation of explanations. Neurocomputing Jesus Antonanzas, Yunzhe Jia, Eibe Frank, Albert Bifet, Bernhard Pfahringer
2022	A*	`conf`	A simple but strong baseline for online continual learning: Repeated Augmented Rehearsal. NeurIPS Yaqian Zhang, Bernhard Pfahringer, Eibe Frank, Albert Bifet, Nick Jin Sean Lim, Yunzhe Jia
2022	J	`jnl`	A simple but strong baseline for online continual learning: Repeated Augmented Rehearsal. CoRR Yaqian Zhang, Bernhard Pfahringer, Eibe Frank, Albert Bifet, Nick Jin Sean Lim, Yunzhe Jia
2022	J	`jnl`	Bandwidth-Optimal Random Shuffling for GPUs. ACM Trans. Parallel Comput. Rory Mitchell, Daniel Stokes, Eibe Frank, Geoffrey Holmes
2022	Misc	`conf`	Better Self-training for Image Classification Through Self-supervision. AI Attaullah Sahito, Eibe Frank, Bernhard Pfahringer
2022	J	`jnl`	Cross-domain Few-shot Meta-learning Using Stacking. CoRR Hongyu Wang, Eibe Frank, Bernhard Pfahringer, Michael Mayo, Geoffrey Holmes
2022	A	`conf`	Efficiently correcting machine learning: considering the role of example ordering in human-in-the-loop training of image classification models. IUI Geoff Holmes, Eibe Frank, Dale Fletcher, Corey Sterling
2022	—	`conf`	Experiments in Cross-domain Few-shot Learning for Image Classification: Extended Abstract. Meta-Knowledge Transfer @ ECML/PKDD Hongyu Wang, Huon Fraser, Henry Gouk, Eibe Frank, Bernhard Pfahringer, Michael Mayo, Geoff Holmes
2022	J	`jnl`	GPUTreeShap: massively parallel exact calculation of SHAP scores for tree ensembles. PeerJ Comput. Sci. Rory Mitchell, Eibe Frank, Geoff Holmes
2022	J	`jnl`	Methods for Eliciting Informative Prior Distributions: A Critical Review. Decis. Anal. Julia R. Falconer, Eibe Frank, Devon L. L. Polaschek, Chaitanya Joshi
2022	J	`jnl`	Sampling Permutations for Shapley Value Estimation. J. Mach. Learn. Res. Rory Mitchell, Joshua Cooper, Eibe Frank, Geoffrey Holmes
2021	J	`jnl`	An Empirical Study of Moment Estimators for Quantile Approximation. ACM Trans. Database Syst. Rory Mitchell, Eibe Frank, Geoffrey Holmes
2021	J	`jnl`	Bandwidth-Optimal Random Shuffling for GPUs. CoRR Rory Mitchell, Daniel Stokes, Eibe Frank, Geoffrey Holmes
2021	J	`jnl`	Better Self-training for Image Classification through Self-supervision. CoRR Attaullah Sahito, Eibe Frank, Bernhard Pfahringer
2021	J	`jnl`	Classifier Chains: A Review and Perspectives. J. Artif. Intell. Res. Jesse Read, Bernhard Pfahringer, Geoff Holmes, Eibe Frank
2021	J	`jnl`	Deep learning in diabetic foot ulcers detection: A comprehensive evaluation. Comput. Biol. Medicine 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
2021	J	`jnl`	Hitting the Target: Stopping Active Learning at the Cost-Based Optimum. CoRR Zac Pullar-Strecker, Katharina Dost, Eibe Frank, Jörg Wicker
2021	Misc	`conf`	Perceptual improvements for Super-Resolution of Satellite Imagery. IVCNZ Daniel Bull, Nick Jin Sean Lim, Eibe Frank
2021	J	`jnl`	Regularisation of neural networks by enforcing Lipschitz continuity. Mach. Learn. Henry Gouk, Eibe Frank, Bernhard Pfahringer, Michael J. Cree
2021	J	`jnl`	Sampling Permutations for Shapley Value Estimation. CoRR Rory Mitchell, Joshua Cooper, Eibe Frank, Geoffrey Holmes
2021	J	`jnl`	Semi-Supervised Learning using Siamese Networks. CoRR Attaullah Sahito, Eibe Frank, Bernhard Pfahringer
2021	—	`conf`	Studying and Exploiting the Relationship Between Model Accuracy and Explanation Quality. ECML/PKDD (2) Yunzhe Jia, Eibe Frank, Bernhard Pfahringer, Albert Bifet, Nick Jin Sean Lim
2021	J	`jnl`	Transfer of Pretrained Model Weights Substantially Improves Semi-Supervised Image Classification. CoRR Attaullah Sahito, Eibe Frank, Bernhard Pfahringer
2020	—	`conf`	A Comparison of Machine Learning Methods for Cross-Domain Few-Shot Learning. Australasian Conference on Artificial Intelligence Hongyu Wang, Henry Gouk, Eibe Frank, Bernhard Pfahringer, Michael Mayo
2020	B	`conf`	Adaptive XGBoost for Evolving Data Streams. IJCNN Jacob Montiel, Rory Mitchell, Eibe Frank, Bernhard Pfahringer, Talel Abdessalem, Albert Bifet
2020	J	`jnl`	Adaptive XGBoost for Evolving Data Streams. CoRR Jacob Montiel, Rory Mitchell, Eibe Frank, Bernhard Pfahringer, Talel Abdessalem, Albert Bifet
2020	J	`jnl`	DFUC2020: Analysis Towards Diabetic Foot Ulcer Detection. CoRR 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
2020	J	`jnl`	Deep Learning in Diabetic Foot Ulcers Detection: A Comprehensive Evaluation. CoRR Moi Hoon Yap, Ryo Hachiuma, Azadeh Alavi, Raphael Brüngel, Manu Goyal, Hongtao Zhu, Bill Cassidy, 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 Pappachan, Claire O'Shea, Eibe Frank
2020	A	`conf`	Embedding Java Classes with code2vec: Improvements from Variable Obfuscation. MSR Rhys Compton, Eibe Frank, Panos Patros, Abigail M. Y. Koay
2020	J	`jnl`	Embedding Java Classes with code2vec: Improvements from Variable Obfuscation. CoRR Rhys Compton, Eibe Frank, Panos Patros, Abigail M. Y. Koay
2020	J	`jnl`	GPUTreeShap: Fast Parallel Tree Interpretability. CoRR Rory Mitchell, Eibe Frank, Geoffrey Holmes
2020	J	`jnl`	Improving Naive Bayes for Regression with Optimized Artificial Surrogate Data. Appl. Artif. Intell. Michael Mayo, Eibe Frank
2020	—	`conf`	Transfer of Pretrained Model Weights Substantially Improves Semi-supervised Image Classification. Australasian Conference on Artificial Intelligence Attaullah Sahito, Eibe Frank, Bernhard Pfahringer
2019	J	`jnl`	AffectiveTweets: a Weka Package for Analyzing Affect in Tweets. J. Mach. Learn. Res. Felipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringer, Saif M. Mohammad
2019	J	`jnl`	Classifier Chains: A Review and Perspectives. CoRR Jesse Read, Bernhard Pfahringer, Geoff Holmes, Eibe Frank
2019	—	`conf`	Ensembles of Nested Dichotomies with Multiple Subset Evaluation. PAKDD (1) Tim Leathart, Eibe Frank, Bernhard Pfahringer, Geoffrey Holmes
2019	—	`conf`	On Calibration of Nested Dichotomies. PAKDD (1) Tim Leathart, Eibe Frank, Bernhard Pfahringer, Geoffrey Holmes
2019	—	`conf`	Semi-supervised Learning Using Siamese Networks. Australasian Conference on Artificial Intelligence Attaullah Sahito, Eibe Frank, Bernhard Pfahringer
2019	C	`conf`	Stochastic Gradient Trees. ACML Henry Gouk, Bernhard Pfahringer, Eibe Frank
2019	J	`jnl`	Stochastic Gradient Trees. CoRR Henry Gouk, Bernhard Pfahringer, Eibe Frank
2019	J	`jnl`	WekaDeeplearning4j: A deep learning package for Weka based on Deeplearning4j. Knowl. Based Syst. Steven Lang, Felipe Bravo-Marquez, Christopher Beckham, Mark Hall, Eibe Frank
2018	J	`jnl`	Ensembles of Nested Dichotomies with Multiple Subset Evaluation. CoRR Tim Leathart, Eibe Frank, Bernhard Pfahringer, Geoffrey Holmes
2018	—	`conf`	Good Vibrations: Artificial Ambience-Based Relay Attack Detection. TrustCom/BigDataSE Iakovos Gurulian, Konstantinos Markantonakis, Eibe Frank, Raja Naeem Akram
2018	Misc	`conf`	Hidden Features: Experiments with Feature Transfer for Fine-Grained Multi-Class and One-Class Image Categorization. IVCNZ Varvara Vetrova, Sheldon Coup, Eibe Frank, Michael J. Cree
2018	—	`conf`	MaxGain: Regularisation of Neural Networks by Constraining Activation Magnitudes. ECML/PKDD (1) Henry Gouk, Bernhard Pfahringer, Eibe Frank, Michael J. Cree
2018	J	`jnl`	MaxGain: Regularisation of Neural Networks by Constraining Activation Magnitudes. CoRR Henry Gouk, Bernhard Pfahringer, Eibe Frank, Michael J. Cree
2018	J	`jnl`	On the Calibration of Nested Dichotomies for Large Multiclass Tasks. CoRR Tim Leathart, Eibe Frank, Bernhard Pfahringer, Geoffrey Holmes
2018	J	`jnl`	Online estimation of discrete, continuous, and conditional joint densities using classifier chains. Data Min. Knowl. Discov. Michael Geilke, Andreas Karwath, Eibe Frank, Stefan Kramer
2018	J	`jnl`	Probability Calibration Trees. CoRR Tim Leathart, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer
2018	J	`jnl`	Regularisation of Neural Networks by Enforcing Lipschitz Continuity. CoRR Henry Gouk, Eibe Frank, Bernhard Pfahringer, Michael J. Cree
2018	J	`jnl`	Transferring sentiment knowledge between words and tweets. Web Intell. Felipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringer
2018	J	`jnl`	XGBoost: Scalable GPU Accelerated Learning. CoRR Rory Mitchell, Andrey Adinets, Thejaswi Rao, Eibe Frank
2017	J	`jnl`	Accelerating the XGBoost algorithm using GPU computing. PeerJ Comput. Sci. Rory Mitchell, Eibe Frank
2017	J	`jnl`	Accelerating the XGBoost algorithm using GPU computing. PeerJ Prepr. Rory Mitchell, Eibe Frank
2017	J	`jnl`	Improving Naive Bayes for Regression with Optimised Artificial Surrogate Data. CoRR Michael Mayo, Eibe Frank
2017	—	`conf`	Large-Scale Automatic Species Identification. Australasian Conference on Artificial Intelligence Jeff Mo, Eibe Frank, Varvara Vetrova
2017	B	`conf`	Learning Through Utility Optimization in Regression Tasks. DSAA Paula Branco, Luís Torgo, Rita P. Ribeiro, Eibe Frank, Bernhard Pfahringer, Markus Michael Rau
2017	—	`conf`	On the Effectiveness of Ambient Sensing for Detecting NFC Relay Attacks. TrustCom/BigDataSE/ICESS Iakovos Gurulian, Carlton Shepherd, Eibe Frank, Konstantinos Markantonakis, Raja Naeem Akram, Keith Mayes
2017	C	`conf`	Probability Calibration Trees. ACML Tim Leathart, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer
2017	—	`conf`	Proximity Assurances Based on Natural and Artificial Ambient Environments. SECITC Iakovos Gurulian, Konstantinos Markantonakis, Carlton Shepherd, Eibe Frank, Raja Naeem Akram
2017	—	`conf`	The Applicability of Ambient Sensors as Proximity Evidence for NFC Transactions. IEEE Symposium on Security and Privacy Workshops Carlton Shepherd, Iakovos Gurulian, Eibe Frank, Konstantinos Markantonakis, Raja Naeem Akram, Emmanouil Panaousis, Keith Mayes
2016	A	`conf`	Annotate-Sample-Average (ASA): A New Distant Supervision Approach for Twitter Sentiment Analysis. ECAI Felipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringer
2016	—	`conf`	Building Ensembles of Adaptive Nested Dichotomies with Random-Pair Selection. ECML/PKDD (2) Tim Leathart, Bernhard Pfahringer, Eibe Frank
2016	J	`jnl`	Building Ensembles of Adaptive Nested Dichotomies with Random-Pair Selection. CoRR Tim Leathart, Bernhard Pfahringer, Eibe Frank
2016	J	`jnl`	Building a Twitter opinion lexicon from automatically-annotated tweets. Knowl. Based Syst. Felipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringer
2016	B	`conf`	Determining Word-Emotion Associations from Tweets by Multi-label Classification. WI Felipe Bravo-Marquez, Eibe Frank, Saif M. Mohammad, Bernhard Pfahringer
2016	B	`conf`	From Opinion Lexicons to Sentiment Classification of Tweets and Vice Versa: A Transfer Learning Approach. WI Felipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringer
2016	—	`ch.`	Introducing Machine Learning Concepts with WEKA. Statistical Genomics Tony C. Smith, Eibe Frank
2015	Misc	`conf`	Alternating model trees. SAC Eibe Frank, Michael Mayo, Stefan Kramer
2015	A*	`conf`	From Unlabelled Tweets to Twitter-specific Opinion Words. SIGIR Felipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringer
2015	A*	`conf`	Positive, Negative, or Neutral: Learning an Expanded Opinion Lexicon from Emoticon-Annotated Tweets. IJCAI Felipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringer
2013	A*	`conf`	Online Estimation of Discrete Densities. ICDM Michael Geilke, Eibe Frank, Andreas Karwath, Stefan Kramer
2013	—	`conf`	Propositionalisation of Multi-instance Data Using Random Forests. Australasian Conference on Artificial Intelligence Eibe Frank, Bernhard Pfahringer
2012	J	`jnl`	Ensembles of Restricted Hoeffding Trees. ACM Trans. Intell. Syst. Technol. Albert Bifet, Eibe Frank, Geoff Holmes, Bernhard Pfahringer
2012	J	`jnl`	Learning a concept-based document similarity measure. J. Assoc. Inf. Sci. Technol. Anna-Lan Huang, David N. Milne, Eibe Frank, Ian H. Witten
2012	J	`jnl`	Locally Weighted Naive Bayes CoRR Eibe Frank, Mark Hall, Bernhard Pfahringer
2011	—	`conf`	Beyond Trees: Adopting MITI to Learn Rules and Ensemble Classifiers for Multi-Instance Data. Australasian Conference on Artificial Intelligence Luke Bjerring, Eibe Frank
2011	J	`jnl`	Classifier chains for multi-label classification. Mach. Learn. Jesse Read, Bernhard Pfahringer, Geoff Holmes, Eibe Frank
2011	—	`book`	Data mining: practical machine learning tools and techniques, 3rd Edition. Ian H. Witten, Eibe Frank, Mark A. Hall
2010	J	`jnl`	A Study of Hierarchical and Flat Classification of Proteins. IEEE ACM Trans. Comput. Biol. Bioinform. Arthur Zimek, Fabian Buchwald, Eibe Frank, Stefan Kramer
2010	J	`jnl`	A review of multi-instance learning assumptions. Knowl. Eng. Rev. James R. Foulds, Eibe Frank
2010	C	`conf`	Accurate Ensembles for Data Streams: Combining Restricted Hoeffding Trees using Stacking. ACML Albert Bifet, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer
2010	A*	`conf`	Fast Conditional Density Estimation for Quantitative Structure-Activity Relationships. AAAI Fabian Buchwald, Tobias Girschick, Eibe Frank, Stefan Kramer
2010	—	`conf`	Fast Perceptron Decision Tree Learning from Evolving Data Streams. PAKDD (2) Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer, Eibe Frank
2010	B	`conf`	Sentiment Knowledge Discovery in Twitter Streaming Data. Discovery Science Albert Bifet, Eibe Frank
2010	B	`conf`	Speeding Up and Boosting Diverse Density Learning. Discovery Science James R. Foulds, Eibe Frank
2010	J	`jnl`	WEKA - Experiences with a Java Open-Source Project. J. Mach. Learn. Res. Remco R. Bouckaert, Eibe Frank, Mark A. Hall, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, Ian H. Witten
2010	—	`ch.`	Weka-A Machine Learning Workbench for Data Mining. Data Mining and Knowledge Discovery Handbook Eibe Frank, Mark Hall, Geoffrey Holmes, Richard Kirkby, Bernhard Pfahringer, Ian H. Witten, Len Trigg
2009	J	`jnl`	Accuracy of machine learning models versus "hand crafted" expert systems - A credit scoring case study. Expert Syst. Appl. Arie Ben-David, Eibe Frank
2009	—	`conf`	Analysing chromatographic data using data mining to monitor petroleum content in water. ITEE Geoffrey Holmes, Dale Fletcher, Peter Reutemann, Eibe Frank
2009	—	`conf`	Classifier Chains for Multi-label Classification. ECML/PKDD (2) Jesse Read, Bernhard Pfahringer, Geoffrey Holmes, Eibe Frank
2009	B	`conf`	Clustering Documents Using a Wikipedia-Based Concept Representation. PAKDD Anna-Lan Huang, David N. Milne, Eibe Frank, Ian H. Witten
2009	C	`conf`	Conditional Density Estimation with Class Probability Estimators. ACML Eibe Frank, Remco R. Bouckaert
2009	A*	`conf`	Human-competitive tagging using automatic keyphrase extraction. EMNLP Olena Medelyan, Eibe Frank, Ian H. Witten
2009	C	`conf`	Large-scale attribute selection using wrappers. CIDM Martin Gütlein, Eibe Frank, Mark Hall, Andreas Karwath
2009	J	`jnl`	The WEKA data mining software: an update. SIGKDD Explor. Mark Hall, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, Ian H. Witten
2008	—	`conf`	Additive Regression Applied to a Large-Scale Collaborative Filtering Problem. Australasian Conference on Artificial Intelligence Eibe Frank, Mark Hall
2008	A*	`conf`	Clustering Documents with Active Learning Using Wikipedia. ICDM Anna-Lan Huang, David N. Milne, Eibe Frank, Ian H. Witten
2008	Misc	`conf`	Combining Naive Bayes and Decision Tables. FLAIRS Mark Hall, Eibe Frank
2008	—	`book`	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
2008	—	`conf`	Discriminating Against New Classes: One-class versus Multi-class Classification. Australasian Conference on Artificial Intelligence Kathryn Hempstalk, Eibe Frank
2008	—	`conf`	One-Class Classification by Combining Density and Class Probability Estimation. ECML/PKDD (1) Kathryn Hempstalk, Eibe Frank, Ian H. Witten
2008	—	`conf`	Revisiting Multiple-Instance Learning Via Embedded Instance Selection. Australasian Conference on Artificial Intelligence James R. Foulds, Eibe Frank
2007	—	`conf`	An Empirical Comparison of Exact Nearest Neighbour Algorithms. PKDD Ashraf M. Kibriya, Eibe Frank
2006	B	`conf`	Improving on Bagging with Input Smearing. PAKDD Eibe Frank, Bernhard Pfahringer
2006	—	`conf`	Naive Bayes for Text Classification with Unbalanced Classes. PKDD Eibe Frank, Remco R. Bouckaert
2005	—	`book`	Data mining - practical machine learning tools and techniques, Second Edition. Ian H. Witten, Eibe Frank
2005	—	`conf`	Ensembles of Balanced Nested Dichotomies for Multi-class Problems. PKDD Lin Dong, Eibe Frank, Stefan Kramer
2005	J	`jnl`	Gene selection from microarray data for cancer classification - a machine learning approach. Comput. Biol. Chem. Yu Wang, Igor V. Tetko, Mark A. Hall, Eibe Frank, Axel Facius, Klaus F. X. Mayer, Hans-Werner Mewes
2005	J	`jnl`	Logistic Model Trees. Mach. Learn. Niels Landwehr, Mark Hall, Eibe Frank
2005	—	`conf`	Speeding Up Logistic Model Tree Induction. PKDD Marc Sumner, Eibe Frank, Mark Hall
2005	—	`conf`	Unsupervised Discretization Using Tree-Based Density Estimation. PKDD Gabi Schmidberger, Eibe Frank
2005	—	`ch.`	WEKA - A Machine Learning Workbench for Data Mining. The Data Mining and Knowledge Discovery Handbook Eibe Frank, Mark A. Hall, Geoffrey Holmes, Richard Kirkby, Bernhard Pfahringer
2004	—	`conf`	A Toolbox for Learning from Relational Data with Propositional and Multi-instance Learners. Australian Conference on Artificial Intelligence Peter Reutemann, Bernhard Pfahringer, Eibe Frank
2004	J	`jnl`	Data mining in bioinformatics using Weka. Bioinform. Eibe Frank, Mark Hall, Leonard E. Trigg, Geoffrey Holmes, Ian H. Witten
2004	A*	`conf`	Ensembles of nested dichotomies for multi-class problems. ICML Eibe Frank, Stefan Kramer
2004	B	`conf`	Evaluating the Replicability of Significance Tests for Comparing Learning Algorithms. PAKDD Remco R. Bouckaert, Eibe Frank
2004	B	`conf`	Logistic Regression and Boosting for Labeled Bags of Instances. PAKDD Xin Xu, Eibe Frank
2004	—	`conf`	Multinomial Naive Bayes for Text Categorization Revisited. Australian Conference on Artificial Intelligence Ashraf M. Kibriya, Eibe Frank, Bernhard Pfahringer, Geoffrey Holmes
2004	J	`jnl`	Predicting Library of Congress classifications from Library of Congress subject headings. J. Assoc. Inf. Sci. Technol. Eibe Frank, Gordon W. Paynter
2004	—	`conf`	Using Classification to Evaluate the Output of Confidence-Based Association Rule Mining. Australian Conference on Artificial Intelligence Stefan Mutter, Mark Hall, Eibe Frank
2003	—	`conf`	A Two-Level Learning Method for Generalized Multi-instance Problems. ECML Nils B. Weidmann, Eibe Frank, Bernhard Pfahringer
2003	A	`conf`	Locally Weighted Naive Bayes. UAI Eibe Frank, Mark A. Hall, Bernhard Pfahringer
2003	—	`conf`	Logistic Model Trees. ECML Niels Landwehr, Mark Hall, Eibe Frank
2003	—	`conf`	Visualizing Class Probability Estimators. PKDD Eibe Frank, Mark Hall
2002	—	`conf`	Multiclass Alternating Decision Trees. ECML Geoffrey Holmes, Bernhard Pfahringer, Richard Kirkby, Eibe Frank, Mark Hall
2002	B	`conf`	Racing Committees for Large Datasets. Discovery Science Eibe Frank, Geoffrey Holmes, Richard Kirkby, Mark Hall
2001	—	`conf`	A Simple Approach to Ordinal Classification. ECML Eibe Frank, Mark Hall
2001	B	`conf`	Determining Progression in Glaucoma Using Visual Fields. PAKDD Andrew Turpin, Eibe Frank, Mark Hall, Ian H. Witten, Chris A. Johnson
2001	J	`jnl`	Interactive machine learning: letting users build classifiers. Int. J. Hum. Comput. Stud. Malcolm Ware, Eibe Frank, Geoffrey Holmes, Mark Hall, Ian H. Witten
2000	—	`conf`	Bottom-Up Propositionalization. ILP Work-in-progress reports Stefan Kramer, Eibe Frank
2000	J	`jnl`	Naive Bayes for Regression (Technical Note). Mach. Learn. Eibe Frank, Leonard E. Trigg, Geoffrey Holmes, Ian H. Witten
2000	B	`conf`	Text Categorization Using Compression Models. Data Compression Conference Eibe Frank, Chang Chui, Ian H. Witten
1999	—	`book`	Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations Ian H. Witten, Eibe Frank
1999	A*	`conf`	Domain-Specific Keyphrase Extraction. IJCAI Eibe Frank, Gordon W. Paynter, Ian H. Witten, Carl Gutwin, Craig G. Nevill-Manning
1999	—	`conf`	Generating Rule Sets from Model Trees. Australian Joint Conference on Artificial Intelligence Geoffrey Holmes, Mark Hall, Eibe Frank
1999	J	`jnl`	Improving browsing in digital libraries with keyphrase indexes. Decis. Support Syst. Carl Gutwin, Gordon W. Paynter, Ian H. Witten, Craig G. Nevill-Manning, Eibe Frank
1999	J	`jnl`	KEA: Practical Automatic Keyphrase Extraction CoRR Ian H. Witten, Gordon W. Paynter, Eibe Frank, Carl Gutwin, Craig G. Nevill-Manning
1999	—	`conf`	KEA: Practical Automatic Keyphrase Extraction. ACM DL Ian H. Witten, Gordon W. Paynter, Eibe Frank, Carl Gutwin, Craig G. Nevill-Manning
1999	A*	`conf`	Making Better Use of Global Discretization. ICML Eibe Frank, Ian H. Witten
1998	A*	`conf`	Generating Accurate Rule Sets Without Global Optimization. ICML Eibe Frank, Ian H. Witten
1998	J	`jnl`	Using Model Trees for Classification. Mach. Learn. Eibe Frank, Yong Wang, Stuart Inglis, Geoffrey Holmes, Ian H. Witten
1998	A*	`conf`	Using a Permutation Test for Attribute Selection in Decision Trees. ICML Eibe Frank, Ian H. Witten