Peter A. Flach

227 papers A* 29A 8B 20C 5Misc 2Journal 95Unranked 56

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Evaluating classification performance across operating contexts: A comparison of decision curve analysis and cost curves. CoRR Louise A. C. Millard, Peter A. Flach
2024	A	`conf`	Explaining a Probabilistic Prediction on the Simplex with Shapley Compositions. ECAI Paul-Gauthier Noé, Miquel Perelló-Nieto, Jean-François Bonastre, Peter A. Flach
2024	J	`jnl`	Explaining a probabilistic prediction on the simplex with Shapley compositions. CoRR Paul-Gauthier Noé, Miquel Perelló-Nieto, Jean-François Bonastre, Peter A. Flach
2024	J	`jnl`	Interpretable representations in explainable AI: from theory to practice. Data Min. Knowl. Discov. Kacper Sokol, Peter A. Flach
2023	J	`jnl`	An active semi-supervised deep learning model for human activity recognition. J. Ambient Intell. Humaniz. Comput. Haixia Bi, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Peter A. Flach, Ian Craddock
2023	J	`jnl`	Classifier calibration: a survey on how to assess and improve predicted class probabilities. Mach. Learn. Telmo de Menezes e Silva Filho, Hao Song, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Meelis Kull, Peter A. Flach
2023	J	`jnl`	Co-designing opportunities for Human-Centred Machine Learning in supporting Type 1 diabetes decision-making. Int. J. Hum. Comput. Stud. Katarzyna Stawarz, Dmitri S. Katz, Amid Ayobi, Paul Marshall, Taku Yamagata, Raúl Santos-Rodríguez, Peter A. Flach, Aisling Ann O'Kane
2023	J	`jnl`	MIDI-Draw: Sketching to Control Melody Generation. CoRR Tashi Namgyal, Peter A. Flach, Raúl Santos-Rodríguez
2023	A	`conf`	Reconciling Training and Evaluation Objectives in Location Agnostic Surrogate Explainers. CIKM Matthew Clifford, Jonathan Erskine, Alexander Hepburn, Peter A. Flach, Raúl Santos-Rodríguez
2023	J	`jnl`	Shapley Sets: Feature Attribution via Recursive Function Decomposition. CoRR Torty Sivill, Peter A. Flach
2023	—	`ch.`	Simply Logical - The First Three Decades. Prolog: The Next 50 Years Peter A. Flach, Kacper Sokol, Jan Wielemaker
2023	—	`conf`	When the Ground Truth is not True: Modelling Human Biases in Temporal Annotations. PerCom Workshops Taku Yamagata, Emma L. Tonkin, Benjamin Arana Sanchez, Ian Craddock, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Weisong Yang, Peter A. Flach
2023	J	`jnl`	When the Ground Truth is not True: Modelling Human Biases in Temporal Annotations. CoRR Taku Yamagata, Emma L. Tonkin, Benjamin Arana Sanchez, Ian Craddock, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Weisong Yang, Peter A. Flach
2022	J	`jnl`	Empirical Evaluation of Predictive Models: A keynote at ECIR 2022. SIGIR Forum Peter A. Flach
2022	J	`jnl`	FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness, Accountability and Transparency Algorithms in Predictive Systems. CoRR Kacper Sokol, Alexander Hepburn, Rafael Poyiadzi, Matthew Clifford, Raúl Santos-Rodríguez, Peter A. Flach
2022	J	`jnl`	FAT Forensics: A Python toolbox for algorithmic fairness, accountability and transparency. Softw. Impacts Kacper Sokol, Raúl Santos-Rodríguez, Peter A. Flach
2022	A	`conf`	LIMESegment: Meaningful, Realistic Time Series Explanations. AISTATS Torty Sivill, Peter A. Flach
2022	—	`conf`	Self-Enhancer: A Self-supervised Framework for Low-Supervision, Drifted Data with Significant Missing Values. ICANN (4) Yu Chen, Peter A. Flach
2022	J	`jnl`	Simply Logical - Intelligent Reasoning by Example (Fully Interactive Online Edition). CoRR Peter A. Flach, Kacper Sokol
2022	—	`conf`	The Weak Supervision Landscape. PerCom Workshops Rafael Poyiadzi, Daniel Bacaicoa-Barber, Jesús Cid-Sueiro, Miquel Perelló-Nieto, Peter A. Flach, Raúl Santos-Rodríguez
2022	J	`jnl`	The Weak Supervision Landscape. CoRR Rafael Poyiadzi, Daniel Bacaicoa-Barber, Jesús Cid-Sueiro, Miquel Perelló-Nieto, Peter A. Flach, Raúl Santos-Rodríguez
2022	—	`conf`	Understanding Reinforcement Learning Based Localisation as a Probabilistic Inference Algorithm. ICANN (2) Taku Yamagata, Raúl Santos-Rodríguez, Robert J. Piechocki, Peter A. Flach
2022	J	`jnl`	What and How of Machine Learning Transparency: Building Bespoke Explainability Tools with Interoperable Algorithmic Components. CoRR Kacper Sokol, Alexander Hepburn, Raúl Santos-Rodríguez, Peter A. Flach
2021	J	`jnl`	CRISP-DM Twenty Years Later: From Data Mining Processes to Data Science Trajectories. IEEE Trans. Knowl. Data Eng. Fernando Martínez-Plumed, Lidia Contreras Ochando, Cèsar Ferri, José Hernández-Orallo, Meelis Kull, Nicolas Lachiche, María José Ramírez-Quintana, Peter A. Flach
2021	J	`jnl`	Classifier Calibration: How to assess and improve predicted class probabilities: a survey. CoRR Telmo de Menezes e Silva Filho, Hao Song, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Meelis Kull, Peter A. Flach
2021	J	`jnl`	Co-Designing Personal Health? Multidisciplinary Benefits and Challenges in Informing Diabetes Self-Care Technologies. Proc. ACM Hum. Comput. Interact. Amid Ayobi, Katarzyna Stawarz, Dmitri S. Katz, Paul Marshall, Taku Yamagata, Raúl Santos-Rodríguez, Peter A. Flach, Aisling Ann O'Kane
2021	J	`jnl`	Continual Density Ratio Estimation in an Online Setting. CoRR Yu Chen, Song Liu, Tom Diethe, Peter A. Flach
2021	J	`jnl`	Efficient and Robust Model Benchmarks with Item Response Theory and Adaptive Testing. Int. J. Interact. Multim. Artif. Intell. Hao Song, Peter A. Flach
2021	J	`jnl`	Explainability Is in the Mind of the Beholder: Establishing the Foundations of Explainable Artificial Intelligence. CoRR Kacper Sokol, Peter A. Flach
2021	J	`jnl`	Human Activity Recognition Based on Dynamic Active Learning. IEEE J. Biomed. Health Informatics Haixia Bi, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Peter A. Flach
2021	—	`conf`	Machine Learning Explanations as Boundary Objects: How AI Researchers Explain and Non-Experts Perceive Machine Learning. IUI Workshops Amid Ayobi, Katarzyna Stawarz, Dmitri S. Katz, Paul Marshall, Taku Yamagata, Raúl Santos-Rodríguez, Peter A. Flach, Aisling Ann O'Kane
2021	J	`jnl`	Multi-label thresholding for cost-sensitive classification. Neurocomputing Reem Alotaibi, Peter A. Flach
2021	J	`jnl`	Risk Sensitive Model-Based Reinforcement Learning using Uncertainty Guided Planning. CoRR Stefan Radic Webster, Peter A. Flach
2021	J	`jnl`	You Only Write Thrice: Creating Documents, Computational Notebooks and Presentations From a Single Source. CoRR Kacper Sokol, Peter A. Flach
2020	J	`jnl`	Bypassing Gradients Re-Projection with Episodic Memories in Online Continual Learning. CoRR Yu Chen, Tom Diethe, Peter A. Flach
2020	—	`conf`	Explainability fact sheets: a framework for systematic assessment of explainable approaches. FAT* Kacper Sokol, Peter A. Flach
2020	C	`conf`	FACE: Feasible and Actionable Counterfactual Explanations. AIES Rafael Poyiadzi, Kacper Sokol, Raúl Santos-Rodríguez, Tijl De Bie, Peter A. Flach
2020	J	`jnl`	FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness, Accountability and Transparency Algorithms in Predictive Systems. J. Open Source Softw. Kacper Sokol, Alexander Hepburn, Rafael Poyiadzi, Matthew Clifford, Raúl Santos-Rodríguez, Peter A. Flach
2020	J	`jnl`	LIMEtree: Interactively Customisable Explanations Based on Local Surrogate Multi-output Regression Trees. CoRR Kacper Sokol, Peter A. Flach
2020	—	`conf`	Model-Based Reinforcement Learning for Type 1 Diabetes Blood Glucose Control. AAI4H@ECAI Taku Yamagata, Aisling Ann O'Kane, Amid Ayobi, Dmitri S. Katz, Katarzyna Stawarz, Paul Marshall, Peter A. Flach, Raúl Santos-Rodríguez
2020	J	`jnl`	Model-Based Reinforcement Learning for Type 1Diabetes Blood Glucose Control. CoRR Taku Yamagata, Aisling Ann O'Kane, Amid Ayobi, Dmitri S. Katz, Katarzyna Stawarz, Paul Marshall, Peter A. Flach, Raúl Santos-Rodríguez
2020	J	`jnl`	Modelling Patient Behaviour Using IoT Sensor Data: a Case Study to Evaluate Techniques for Modelling Domestic Behaviour in Recovery from Total Hip Replacement Surgery. J. Heal. Informatics Res. Michael Holmes, Miquel Perelló-Nieto, Hao Song, Emma Tonkin, Sabrina Grant, Peter A. Flach
2020	J	`jnl`	One Explanation Does Not Fit All. Künstliche Intell. Kacper Sokol, Peter A. Flach
2020	J	`jnl`	One Explanation Does Not Fit All: The Promise of Interactive Explanations for Machine Learning Transparency. CoRR Kacper Sokol, Peter A. Flach
2020	C	`conf`	Polsar Image Classification via Robust Low-Rank Feature Extraction and Markov Random Field. IGARSS Haixia Bi, Raúl Santos-Rodríguez, Peter A. Flach
2020	J	`jnl`	Reflections on reciprocity in research. Mach. Learn. Peter A. Flach
2020	J	`jnl`	Towards Faithful and Meaningful Interpretable Representations. CoRR Kacper Sokol, Peter A. Flach
2020	J	`jnl`	Uni- and multivariate probability density models for numeric subgroup discovery. Intell. Data Anal. Marvin Meeng, Harm de Vries, Peter A. Flach, Siegfried Nijssen, Arno J. Knobbe
2019	A	`conf`	$β^3$-IRT: A New Item Response Model and its Applications. AISTATS Yu Chen, Telmo de Menezes e Silva Filho, Ricardo B. C. Prudêncio, Tom Diethe, Peter A. Flach
2019	J	`jnl`	A Big Data platform for smart meter data analytics. Comput. Ind. Tom Wilcox, Nanlin Jin, Peter A. Flach, Joshua Thumim
2019	J	`jnl`	An application of hierarchical Gaussian processes to the detection of anomalies in star light curves. Neurocomputing Niall Twomey, Haoyan Chen, Tom Diethe, Peter A. Flach
2019	A*	`conf`	Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration. NeurIPS Meelis Kull, Miquel Perelló-Nieto, Markus Kängsepp, Telmo de Menezes e Silva Filho, Hao Song, Peter A. Flach
2019	J	`jnl`	Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration. CoRR Meelis Kull, Miquel Perelló-Nieto, Markus Kängsepp, Telmo de Menezes e Silva Filho, Hao Song, Peter A. Flach
2019	—	`conf`	Counterfactual Explanations of Machine Learning Predictions: Opportunities and Challenges for AI Safety. SafeAI@AAAI Kacper Sokol, Peter A. Flach
2019	A*	`conf`	Desiderata for Interpretability: Explaining Decision Tree Predictions with Counterfactuals. AAAI Kacper Sokol, Peter A. Flach
2019	J	`jnl`	Distribution Calibration for Regression. CoRR Hao Song, Tom Diethe, Meelis Kull, Peter A. Flach
2019	A*	`conf`	Distribution calibration for regression. ICML Hao Song, Tom Diethe, Meelis Kull, Peter A. Flach
2019	J	`jnl`	Explainability Fact Sheets: A Framework for Systematic Assessment of Explainable Approaches. CoRR Kacper Sokol, Peter A. Flach
2019	J	`jnl`	FACE: Feasible and Actionable Counterfactual Explanations. CoRR Rafael Poyiadzi, Kacper Sokol, Raúl Santos-Rodriguez, Tijl De Bie, Peter A. Flach
2019	J	`jnl`	FAT Forensics: A Python Toolbox for Algorithmic Fairness, Accountability and Transparency. CoRR Kacper Sokol, Raúl Santos-Rodríguez, Peter A. Flach
2019	J	`jnl`	HyperStream: a Workflow Engine for Streaming Data. CoRR Tom Diethe, Meelis Kull, Niall Twomey, Kacper Sokol, Hao Song, Miquel Perelló-Nieto, Emma Tonkin, Peter A. Flach
2019	A*	`conf`	Performance Evaluation in Machine Learning: The Good, the Bad, the Ugly, and the Way Forward. AAAI Peter A. Flach
2019	J	`jnl`	Setting decision thresholds when operating conditions are uncertain. Data Min. Knowl. Discov. Cèsar Ferri, José Hernández-Orallo, Peter A. Flach
2019	J	`jnl`	bLIMEy: Surrogate Prediction Explanations Beyond LIME. CoRR Kacper Sokol, Alexander Hepburn, Raúl Santos-Rodríguez, Peter A. Flach
2019	J	`jnl`	β CoRR Yu Chen, Telmo de Menezes e Silva Filho, Ricardo B. C. Prudêncio, Tom Diethe, Peter A. Flach
2018	J	`jnl`	A Comprehensive Study of Activity Recognition Using Accelerometers. Informatics Niall Twomey, Tom Diethe, Xenofon Fafoutis, Atis Elsts, Ryan McConville, Peter A. Flach, Ian Craddock
2018	J	`jnl`	Activities of Daily Living Ontology for Ubiquitous Systems: Development and Evaluation. Sensors Przemyslaw Woznowski, Emma Tonkin, Peter A. Flach
2018	—	`conf`	Analysis of Patient Domestic Activity in Recovery From Hip or Knee RePlacement Surgery: Modelling Wrist-worn Wearable RSSI and Accelerometer Data in The Wild. KDH@IJCAI Mike Holmes, Hao Song, Emma Tonkin, Miquel Perelló-Nieto, Sabrina Grant, Peter A. Flach
2018	B	`conf`	Anomaly detection in star light curves using hierarchical Gaussian processes. ESANN Haoyan Chen, Tom Diethe, Niall Twomey, Peter A. Flach
2018	A*	`conf`	Conversational Explanations of Machine Learning Predictions Through Class-contrastive Counterfactual Statements. IJCAI Kacper Sokol, Peter A. Flach
2018	A*	`conf`	Glass-Box: Explaining AI Decisions With Counterfactual Statements Through Conversation With a Voice-enabled Virtual Assistant. IJCAI Kacper Sokol, Peter A. Flach
2018	J	`jnl`	Introduction to the special issue on Data Science in Europe. Int. J. Data Sci. Anal. Peter A. Flach, Myra Spiliopoulou, Serge Allegrezza, Matthias Böhmer, Burkhard Hess, Berthold Lausen
2018	J	`jnl`	Non-Parametric Calibration of Probabilistic Regression. CoRR Hao Song, Meelis Kull, Peter A. Flach
2018	A*	`conf`	Releasing eHealth Analytics into the Wild: Lessons Learnt from the SPHERE Project. KDD Tom Diethe, Mike Holmes, Meelis Kull, Miquel Perelló-Nieto, Kacper Sokol, Hao Song, Emma Tonkin, Niall Twomey, Peter A. Flach
2018	A*	`conf`	The Facets of Artificial Intelligence: A Framework to Track the Evolution of AI. IJCAI Fernando Martínez-Plumed, Bao Sheng Loe, Peter A. Flach, Seán Ó hÉigeartaigh, Karina Vold, José Hernández-Orallo
2017	A	`conf`	Beta calibration: a well-founded and easily implemented improvement on logistic calibration for binary classifiers. AISTATS Meelis Kull, Telmo de Menezes e Silva Filho, Peter A. Flach
2017	J	`jnl`	CASP-DM: Context Aware Standard Process for Data Mining. CoRR Fernando Martínez-Plumed, Lidia Contreras Ochando, César Ferri, Peter A. Flach, José Hernández-Orallo, Meelis Kull, Nicolas Lachiche, María José Ramírez-Quintana
2017	—	`ch.`	Classifier Calibration. Encyclopedia of Machine Learning and Data Mining Peter A. Flach
2017	J	`jnl`	Computational support for academic peer review: a perspective from artificial intelligence. Commun. ACM Simon Price, Peter A. Flach
2017	—	`ch.`	First-Order Logic. Encyclopedia of Machine Learning and Data Mining Peter A. Flach
2017	J	`jnl`	Probabilistic Sensor Fusion for Ambient Assisted Living. CoRR Tom Diethe, Niall Twomey, Meelis Kull, Peter A. Flach, Ian Craddock
2017	—	`ch.`	ROC Analysis. Encyclopedia of Machine Learning and Data Mining Peter A. Flach
2017	A*	`conf`	The Role of Textualisation and Argumentation in Understanding the Machine Learning Process. IJCAI Kacper Sokol, Peter A. Flach
2017	J	`jnl`	Unsupervised learning of sensor topologies for improving activity recognition in smart environments. Neurocomputing Niall Twomey, Tom Diethe, Ian Craddock, Peter A. Flach
2016	A*	`conf`	ADL™: A Topic Model for Discovery of Activities of Daily Living in a Smart Home. IJCAI Yu Chen, Tom Diethe, Peter A. Flach
2016	B	`conf`	Active transfer learning for activity recognition. ESANN Tom Diethe, Niall Twomey, Peter A. Flach
2016	—	`conf`	Activity Recognition in Multiple Contexts for Smart-House Data. ILP (Short Papers) Kacper Sokol, Peter A. Flach
2016	—	`conf`	BDL.NET: Bayesian dictionary learning in Infer.NET. MLSP Tom Diethe, Niall Twomey, Peter A. Flach
2016	A*	`conf`	Background Check: A General Technique to Build More Reliable and Versatile Classifiers. ICDM Miquel Perelló-Nieto, Telmo de Menezes e Silva Filho, Meelis Kull, Peter A. Flach
2016	J	`jnl`	Cost-sensitive boosting algorithms: Do we really need them? Mach. Learn. Nikolaos Nikolaou, Narayanan Unny Edakunni, Meelis Kull, Peter A. Flach, Gavin Brown
2016	A	`conf`	Declaratively Capturing Local Label Correlations with Multi-Label Trees. ECAI Reem Al-Otaibi, Meelis Kull, Peter A. Flach
2016	A*	`conf`	Fast Unsupervised Online Drift Detection Using Incremental Kolmogorov-Smirnov Test. KDD Denis Moreira dos Reis, Peter A. Flach, Stan Matwin, Gustavo E. A. P. A. Batista
2016	J	`jnl`	Feature Construction and Calibration for Clustering Daily Load Curves from Smart-Meter Data. IEEE Trans. Ind. Informatics Reem Al-Otaibi, Nanlin Jin, Tom Wilcox, Peter A. Flach
2016	J	`jnl`	On the need for structure modelling in sequence prediction. Mach. Learn. Niall Twomey, Tom Diethe, Peter A. Flach
2016	J	`jnl`	Reframing in context: A systematic approach for model reuse in machine learning. AI Commun. José Hernández-Orallo, Adolfo Martínez Usó, Ricardo B. C. Prudêncio, Meelis Kull, Peter A. Flach, Chowdhury Farhan Ahmed, Nicolas Lachiche
2016	—	`conf`	Subgroup Discovery with Proper Scoring Rules. ECML/PKDD (2) Hao Song, Meelis Kull, Peter A. Flach, Georgios Kalogridis
2016	J	`jnl`	The SPHERE Challenge: Activity Recognition with Multimodal Sensor Data. CoRR Niall Twomey, Tom Diethe, Meelis Kull, Hao Song, Massimo Camplani, Sion L. Hannuna, Xenofon Fafoutis, Ni Zhu, Pete Woznowski, Peter A. Flach, Ian Craddock
2015	—	`conf`	Activity recognition using conditional random field. iWOAR Megha Agarwal, Peter A. Flach
2015	—	`conf`	Bayesian Modelling of the Temporal Aspects of Smart Home Activity with Circular Statistics. ECML/PKDD (2) Tom Diethe, Niall Twomey, Peter A. Flach
2015	J	`jnl`	Bridging e-Health and the Internet of Things: The SPHERE Project. IEEE Intell. Syst. Ni Zhu, Tom Diethe, Massimo Camplani, Lili Tao, Alison Burrows, Niall Twomey, Dritan Kaleshi, Majid Mirmehdi, Peter A. Flach, Ian Craddock
2015	—	`conf`	Model Reuse with Subgroup Discovery. DC@PKDD/ECML Hao Song, Peter A. Flach
2015	—	`conf`	Novel Decompositions of Proper Scoring Rules for Classification: Score Adjustment as Precursor to Calibration. ECML/PKDD (1) Meelis Kull, Peter A. Flach
2015	—	`conf`	Precision-Recall-Gain Curves: PR Analysis Done Right. NIPS Peter A. Flach, Meelis Kull
2015	B	`conf`	Reframing in Frequent Pattern Mining. ICTAI Chowdhury Farhan Ahmed, Md. Samiullah, Nicolas Lachiche, Meelis Kull, Peter A. Flach
2015	J	`jnl`	Report of the First International Workshop on Learning over Multiple Contexts (LMCE 2014). SIGKDD Explor. Cèsar Ferri Ramirez, Peter A. Flach, Nicolas Lachiche
2015	—	`conf`	SVR-based Modelling for the MoReBikeS Challenge: Analysis, Visualisation and Prediction. DC@PKDD/ECML Yu Chen, Peter A. Flach
2015	—	`conf`	Versatile Decision Trees for Learning Over Multiple Contexts. ECML/PKDD (1) Reem Al-Otaibi, Ricardo B. C. Prudêncio, Meelis Kull, Peter A. Flach
2014	Misc	`conf`	A Machine Learning Approach to Objective Cardiac Event Detection. CISIS Niall Twomey, Peter A. Flach
2014	C	`conf`	LaCova: A Tree-Based Multi-label Classifier Using Label Covariance as Splitting Criterion. ICMLA Reem Al-Otaibi, Meelis Kull, Peter A. Flach
2014	—	`conf`	Rate-Constrained Ranking and the Rate-Weighted AUC. ECML/PKDD (2) Louise A. C. Millard, Peter A. Flach, Julian P. T. Higgins
2014	—	`conf`	Rate-Oriented Point-Wise Confidence Bounds for ROC Curves. ECML/PKDD (2) Louise A. C. Millard, Meelis Kull, Peter A. Flach
2014	—	`conf`	Reliability Maps: A Tool to Enhance Probability Estimates and Improve Classification Accuracy. ECML/PKDD (2) Meelis Kull, Peter A. Flach
2014	J	`jnl`	Subgroup Discovery in Smart Electricity Meter Data. IEEE Trans. Ind. Informatics Nanlin Jin, Peter A. Flach, Tom Wilcox, Royston Sellman, Joshua Thumim, Arno J. Knobbe
2013	—	`conf`	A Higher-order data flow model for heterogeneous Big Data. IEEE BigData Simon Price, Peter A. Flach
2013	J	`jnl`	Guest editors' introduction: special issue of selected papers from ECML-PKDD 2012. Mach. Learn. Tijl De Bie, Peter A. Flach
2013	J	`jnl`	Guest editors' introduction: special section of selected papers from ECML-PKDD 2012. Data Min. Knowl. Discov. Tijl De Bie, Peter A. Flach
2013	J	`jnl`	ROC curves in cost space. Mach. Learn. José Hernández-Orallo, Peter A. Flach, César Ferri
2013	J	`jnl`	SubSift web services and workflows for profiling and comparing scientists and their published works. Future Gener. Comput. Syst. Simon Price, Peter A. Flach, Sebastian Spiegler, Christopher Bailey, Nikki Rogers
2012	J	`jnl`	A unified view of performance metrics: translating threshold choice into expected classification loss. J. Mach. Learn. Res. José Hernández-Orallo, Peter A. Flach, César Ferri
2012	J	`jnl`	Caveats and pitfalls of ROC analysis in clinical microarray research (and how to avoid them). Briefings Bioinform. Daniel P. Berrar, Peter A. Flach
2012	J	`jnl`	ILP turns 20 - Biography and future challenges. Mach. Learn. Stephen H. Muggleton, Luc De Raedt, David Poole, Ivan Bratko, Peter A. Flach, Katsumi Inoue, Ashwin Srinivasan
2012	—	`book`	Machine Learning - The Art and Science of Algorithms that Make Sense of Data. Peter A. Flach
2012	—	`ed.`	Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2012, Bristol, UK, September 24-28, 2012. Proceedings, Part I ECML/PKDD (1) Peter A. Flach, Tijl De Bie, Nello Cristianini
2012	—	`ed.`	Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2012, Bristol, UK, September 24-28, 2012. Proceedings, Part II ECML/PKDD (2) Peter A. Flach, Tijl De Bie, Nello Cristianini
2011	A*	`conf`	A Coherent Interpretation of AUC as a Measure of Aggregated Classification Performance. ICML Peter A. Flach, José Hernández-Orallo, Cèsar Ferri Ramirez
2011	A*	`conf`	Brier Curves: a New Cost-Based Visualisation of Classifier Performance. ICML José Hernández-Orallo, Peter A. Flach, Cèsar Ferri Ramirez
2011	J	`jnl`	Generic Multiplicative Methods for Implementing Machine Learning Algorithms on MapReduce CoRR Song Liu, Peter A. Flach, Nello Cristianini
2011	—	`conf`	Smooth Receiver Operating Characteristics (smROC) Curves. ECML/PKDD (2) William Klement, Peter A. Flach, Nathalie Japkowicz, Stan Matwin
2011	J	`jnl`	Technical Note: Towards ROC Curves in Cost Space CoRR José Hernández-Orallo, Peter A. Flach, Cèsar Ferri Ramirez
2011	J	`jnl`	The Machine Learning journal: 25 years young. Mach. Learn. Peter A. Flach
2011	J	`jnl`	Threshold Choice Methods: the Missing Link CoRR José Hernández-Orallo, Peter A. Flach, César Ferri
2010	A*	`conf`	Enhanced Word Decomposition by Calibrating the Decision Threshold of Probabilistic Models and Using a Model Ensemble. ACL Sebastian Spiegler, Peter A. Flach
2010	C	`conf`	Exploiting the High Predictive Power of Multi-class Subgroups. ACML Tarek Abudawood, Peter A. Flach
2010	—	`ch.`	First-Order Logic. Encyclopedia of Machine Learning Peter A. Flach
2010	—	`conf`	First-Order Multi-class Subgroup Discovery. STAIRS Tarek Abudawood, Peter A. Flach
2010	B	`conf`	Learning Multi-class Theories in ILP. ILP Tarek Abudawood, Peter A. Flach
2010	—	`ch.`	ROC Analysis. Encyclopedia of Machine Learning Peter A. Flach
2010	—	`conf`	SubSift Web Services and Workflows for Profiling and Comparing Scientists and Their Published Works. eScience Simon Price, Peter A. Flach, Sebastian Spiegler, Christopher Bailey, Nikki Rogers
2010	—	`conf`	SubSift: a novel application of the vector space model to support the academic research process. WAPA Simon Price, Peter A. Flach, Sebastian Spiegler
2010	A	`conf`	The Advantages of Seed Examples in First-Order Multi-class Subgroup Discovery. ECAI Tarek Abudawood, Peter A. Flach
2010	J	`jnl`	The Machine Learning journal: 250 issues and counting. Mach. Learn. Peter A. Flach
2010	B	`conf`	Ukwabelana - An open-source morphological Zulu corpus. COLING Sebastian Spiegler, Andrew van der Spuy, Peter A. Flach
2009	J	`jnl`	Abduction and Induction in Artificial Intelligence. J. Appl. Log. Antonis C. Kakas, Peter A. Flach
2009	—	`conf`	Cost-Based Sampling of Individual Instances. Canadian AI William Klement, Peter A. Flach, Nathalie Japkowicz, Stan Matwin
2009	—	`conf`	Evaluation Measures for Multi-class Subgroup Discovery. ECML/PKDD (1) Tarek Abudawood, Peter A. Flach
2009	J	`jnl`	Novel tools to streamline the conference review process: experiences from SIGKDD'09. SIGKDD Explor. Peter A. Flach, Sebastian Spiegler, Bruno Golénia, Simon Price, John Guiver, Ralf Herbrich, Thore Graepel, Mohammed J. Zaki
2009	—	`conf`	PROMODES: A Probabilistic Generative Model for Word Decomposition. CLEF (Working Notes) Sebastian Spiegler, Bruno Golénia, Peter A. Flach
2009	A*	`ed.`	Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28 - July 1, 2009 KDD John F. Elder IV, Françoise Fogelman-Soulié, Peter A. Flach, Mohammed Javeed Zaki
2009	J	`jnl`	Towards Learning Morphology for Under-Resourced Fusional and Agglutinating Languages. IEEE Trans. Speech Audio Process. Kseniya B. Shalonova, Bruno Golénia, Peter A. Flach
2009	—	`conf`	UNGRADE: UNsupervised GRAph DEcomposition. CLEF (Working Notes) Bruno Golénia, Sebastian Spiegler, Peter A. Flach
2009	—	`conf`	Unsupervised Morpheme Discovery with Ungrade. CLEF (1) Bruno Golénia, Sebastian Spiegler, Peter A. Flach
2009	—	`conf`	Unsupervised Word Decomposition with the Promodes Algorithm. CLEF (1) Sebastian Spiegler, Bruno Golénia, Peter A. Flach
2009	—	`conf`	Using Time Dependent Link Reduction to Improve the Efficiency of Topic Prediction in Co-Authorship Graphs. CompleNet Susanne Hoche, David Hardcastle, Peter A. Flach
2008	A	`conf`	A Fast Method for Property Prediction in Graph-Structured Data from Positive and Unlabelled Examples. ECAI Susanne Hoche, Peter A. Flach, David Hardcastle
2008	—	`conf`	Learning the morphology of Zulu with different degrees of supervision. SLT Sebastian Spiegler, Bruno Golénia, Ksenia Shalonova, Peter A. Flach, Roger C. F. Tucker
2008	B	`conf`	Querying and Merging Heterogeneous Data by Approximate Joins on Higher-Order Terms. ILP Simon Price, Peter A. Flach
2007	—	`conf`	A Simple Lexicographic Ranker and Probability Estimator. ECML Peter A. Flach, Edson Takashi Matsubara
2007	—	`conf`	An Improved Model Selection Heuristic for AUC. ECML Shaomin Wu, Peter A. Flach, Cèsar Ferri Ramirez
2007	J	`jnl`	Network analysis in natural sciences and engineering. AI Commun. Susanne Hoche, Andreas Nürnberger, Peter A. Flach
2007	—	`conf`	On classification, ranking, and probability estimation. Probabilistic, Logical and Relational Learning - A Further Synthesis Peter A. Flach, Edson Takashi Matsubara
2007	—	`conf`	Putting Things in Order: On the Fundamental Role of Ranking in Classification and Probability Estimation. ECML/PKDD Peter A. Flach
2006	—	`conf`	Reinventing Machine Learning with ROC Analysis. IBERAMIA-SBIA Peter A. Flach
2006	B	`conf`	Towards Automating Simulation-Based Design Verification Using ILP. ILP Kerstin Eder, Peter A. Flach, Hsiou-Wen Hsueh
2005	J	`jnl`	A Response to Webb and Ting's Mach. Learn. Tom Fawcett, Peter A. Flach
2005	—	`conf`	Combining Bayesian Networks with Higher-Order Data Representations. Probabilistic, Logical and Relational Learning Elias Gyftodimos, Peter A. Flach
2005	B	`conf`	Combining Bayesian Networks with Higher-Order Data Representations. IDA Elias Gyftodimos, Peter A. Flach
2005	J	`jnl`	ROC 'n' Rule Learning - Towards a Better Understanding of Covering Algorithms. Mach. Learn. Johannes Fürnkranz, Peter A. Flach
2005	A*	`conf`	ROCCER: An Algorithm for Rule Learning Based on ROC Analysis. IJCAI Ronaldo C. Prati, Peter A. Flach
2005	A*	`conf`	Repairing Concavities in ROC Curves. IJCAI Peter A. Flach, Shaomin Wu
2004	—	`conf`	An Analysis of Stopping and Filtering Criteria for Rule Learning. ECML Johannes Fürnkranz, Peter A. Flach
2004	J	`jnl`	Book review: Logic for Learning: Learning Comprehensible Theories from Structured Data by John W. Lloyd, Springer-Verlag, 2003, ISBN 3-540-42027-4. Theory Pract. Log. Program. Peter A. Flach
2004	J	`jnl`	Decision Support Through Subgroup Discovery: Three Case Studies and the Lessons Learned. Mach. Learn. Nada Lavrac, Bojan Cestnik, Dragan Gamberger, Peter A. Flach
2004	A*	`conf`	Delegating classifiers. ICML César Ferri, Peter A. Flach, José Hernández-Orallo
2004	—	`conf`	Hierarchical Bayesian Networks: An Approach to Classification and Learning for Structured Data. SETN Elias Gyftodimos, Peter A. Flach
2004	J	`jnl`	Kernels and Distances for Structured Data. Mach. Learn. Thomas Gärtner, John W. Lloyd, Peter A. Flach
2004	J	`jnl`	Naive Bayesian Classification of Structured Data. Mach. Learn. Peter A. Flach, Nicolas Lachiche
2004	—	`ed.`	ROC Analysis in Artificial Intelligence, 1st International Workshop, ROCAI-2004, Valencia, Spain, August 22, 2004 ROCAI José Hernández-Orallo, César Ferri, Nicolas Lachiche, Peter A. Flach
2004	A*	`conf`	Redundant feature elimination for multi-class problems. ICML Annalisa Appice, Michelangelo Ceci, Simon Alan Rawles, Peter A. Flach
2004	J	`jnl`	Subgroup Discovery with CN2-SD. J. Mach. Learn. Res. Nada Lavrac, Branko Kavsek, Peter A. Flach, Ljupco Todorovski
2004	J	`jnl`	The 1st workshop on ROC analysis in artificial intelligence (ROCAI-2004). SIGKDD Explor. José Hernández-Orallo, César Ferri, Nicolas Lachiche, Peter A. Flach
2003	A*	`conf`	An Analysis of Rule Evaluation Metrics. ICML Johannes Fürnkranz, Peter A. Flach
2003	B	`conf`	Comparative Evaluation of Approaches to Propositionalization. ILP Mark-A. Krogel, Simon Alan Rawles, Filip Zelezný, Peter A. Flach, Nada Lavrac, Stefan Wrobel
2003	B	`conf`	Improved Distances for Structured Data. ILP Dimitrios Mavroeidis, Peter A. Flach
2003	A*	`conf`	Improving Accuracy and Cost of Two-class and Multi-class Probabilistic Classifiers Using ROC Curves. ICML Nicolas Lachiche, Peter A. Flach
2003	—	`conf`	Improving the AUC of Probabilistic Estimation Trees. ECML César Ferri, Peter A. Flach, José Hernández-Orallo
2003	A*	`conf`	On Graph Kernels: Hardness Results and Efficient Alternatives. COLT Thomas Gärtner, Peter A. Flach, Stefan Wrobel
2003	A*	`conf`	The Geometry of ROC Space: Understanding Machine Learning Metrics through ROC Isometrics. ICML Peter A. Flach
2002	B	`conf`	1BC2: A True First-Order Bayesian Classifier. ILP Nicolas Lachiche, Peter A. Flach
2002	A*	`conf`	Adapting classification rule induction to subgroup discovery. ICDM Nada Lavrac, Peter A. Flach, Branko Kavsek, Ljupco Todorovski
2002	B	`conf`	Improved Dataset Characterisation for Meta-learning. Discovery Science Yonghong Peng, Peter A. Flach, Carlos Soares, Pavel Brazdil
2002	B	`conf`	Kernels for Structured Data. ILP Thomas Gärtner, John W. Lloyd, Peter A. Flach
2002	A*	`conf`	Learning Decision Trees Using the Area Under the ROC Curve. ICML César Ferri, Peter A. Flach, José Hernández-Orallo
2002	—	`conf`	Learning in Clausal Logic: A Perspective on Inductive Logic Programming. Computational Logic: Logic Programming and Beyond Peter A. Flach, Nada Lavrac
2002	A*	`conf`	Multi-Instance Kernels. ICML Thomas Gärtner, Peter A. Flach, Adam Kowalczyk, Alexander J. Smola
2002	B	`conf`	RSD: Relational Subgroup Discovery through First-Order Feature Construction. ILP Nada Lavrac, Filip Zelezný, Peter A. Flach
2002	J	`jnl`	Web-based analysis of data mining and decision support education. AI Commun. Tanja Urbancic, Maja Skrjanc, Peter A. Flach
2001	J	`jnl`	An extended transformation approach to inductive logic programming. ACM Trans. Comput. Log. Nada Lavrac, Peter A. Flach
2001	J	`jnl`	Confirmation-Guided Discovery of First-Order Rules with Tertius. Mach. Learn. Peter A. Flach, Nicolas Lachiche
2001	J	`jnl`	Editorial: Inductive Logic Programming is Coming of Age. Mach. Learn. Peter A. Flach, Saso Dzeroski
2001	—	`ed.`	Machine Learning: EMCL 2001, 12th European Conference on Machine Learning, Freiburg, Germany, September 5-7, 2001, Proceedings ECML Luc De Raedt, Peter A. Flach
2001	Misc	`conf`	Multi-relational Data Mining: a perspective. EPIA Peter A. Flach
2001	J	`jnl`	On the state of the art in machine learning: A personal review. Artif. Intell. Peter A. Flach
2001	A*	`conf`	WBCsvm: Weighted Bayesian Classification based on Support Vector Machines. ICML Thomas Gärtner, Peter A. Flach
2000	—	`conf`	Decomposing Probability Distributions on Structured Individuals. ILP Work-in-progress reports Peter A. Flach, Nicolas Lachiche
2000	J	`jnl`	Discovery of multivalued dependencies from relations. Intell. Data Anal. Iztok Savnik, Peter A. Flach
2000	—	`conf`	Predictive Performance of Weghted Relative Accuracy. PKDD Ljupco Todorovski, Peter A. Flach, Nada Lavrac
2000	—	`conf`	The Use of Functional and Logic Languages in Machine Learning. WFLP Peter A. Flach
1999	J	`jnl`	Database Dependency Discovery: A Machine Learning Approach. AI Commun. Peter A. Flach, Iztok Savnik
1999	B	`conf`	IBC: A First-Order Bayesian Classifier. ILP Peter A. Flach, Nicolas Lachiche
1999	B	`ed.`	Inductive Logic Programming, 9th International Workshop, ILP-99, Bled, Slovenia, June 24-27, 1999, Proceedings ILP Saso Dzeroski, Peter A. Flach
1999	—	`conf`	Knowledge Representation for Inductive Learning. ESCQARU Peter A. Flach
1999	B	`conf`	Rule Evaluation Measures: A Unifying View. ILP Nada Lavrac, Peter A. Flach, Blaz Zupan
1998	A*	`conf`	Comparing Consequence Relations. KR Peter A. Flach
1998	J	`jnl`	Conference Report: Abduction and Induction in AI; Logic, Proofs and Algorithms; Logic in Natural Language; Logic for Concurrency and Synchronisation (LOCUS). Log. J. IGPL Peter A. Flach, Antonis C. Kakas, Ruy J. G. B. de Queiroz, Katia Silva Guimarães
1998	—	`conf`	From Extensional to Intensional Knowledge: Inductive Logic Programming Techniques and Their Application to Deductive Databases. Transactions and Change in Logic Databases Peter A. Flach
1998	B	`conf`	Strongly Typed Inductive Concept Learning. ILP Peter A. Flach, Christophe G. Giraud-Carrier, John W. Lloyd
1997	J	`jnl`	Abductive and Inductive Reasoning: Report of the ECAI'96 Workshop. Log. J. IGPL Peter A. Flach, Antonis C. Kakas
1997	—	`conf`	Inductive Logic Databases: From Extensional to Intensional Knowledge. DOOD Peter A. Flach
1997	B	`conf`	Normal Forms for Inductive Logic Programming. ILP Peter A. Flach
1996	B	`conf`	Rationality Postulates for Induction. TARK Peter A. Flach
1994	—	`book`	Simply logical - intelligent reasoning by example. Peter A. Flach
1993	—	`conf`	Predicate Invention in Inductive Data Engineering. ECML Peter A. Flach
1992	—	`conf`	A Model of Inductive Reasoning. Logic at Work Peter A. Flach
1992	—	`conf`	An Analysis of Various Forms of "Jumping to Conclusions". AII Peter A. Flach
1991	—	`conf`	Consistent Term Mappings, Term Partitions and Inverse Resolution. EWSL Shan-Hwei Nienhuys-Cheng, Peter A. Flach
1991	C	`conf`	Towards a Theory of Inductive Logic Programming. ISMIS Peter A. Flach
1989	—	`conf`	Second-order Inductive Learning. AII Peter A. Flach