Notes on the H-measure of classifier performance.

Christoforos Anagnostopoulos https://orcid.org/0000-0002-6001-9921 https://www.wikidata.org/entity/Q95944425

David J. Hand Christoforos Anagnostopoulos Notes on the H-measure of classifier performance. 109-124 2023 March 17 Adv. Data Anal. Classif. 1 https://doi.org/10.1007/s11634-021-00490-3 db/journals/adac/adac17.html#HandA23

David J. Hand Christoforos Anagnostopoulos Notes on the H-measure of classifier performance. 2021 abs/2106.11888 CoRR https://arxiv.org/abs/2106.11888 db/journals/corr/corr2106.html#abs-2106-11888

Ricardo Pio Monti Christoforos Anagnostopoulos Giovanni Montana Adaptive regularization for Lasso models in the context of nonstationary data streams. 237-247 2018 11 Stat. Anal. Data Min. 5 https://doi.org/10.1002/sam.11390 https://www.wikidata.org/entity/Q129560730 db/journals/sadm/sadm11.html#MontiAM18

Ricardo Pio Monti Romy Lorenz Peter Hellyer Robert Leech Christoforos Anagnostopoulos Giovanni Montana Decoding Time-Varying Functional Connectivity Networks via Linear Graph Embedding Methods. 2017 11 Frontiers Comput. Neurosci. https://doi.org/10.3389/fncom.2017.00014 https://www.wikidata.org/entity/Q38857326 db/journals/ficn/ficn11.html#MontiLHLAM17 14

Romy Lorenz Ricardo Pio Monti Inês R. Violante Christoforos Anagnostopoulos Aldo A. Faisal Giovanni Montana Robert Leech The Automatic Neuroscientist: A framework for optimizing experimental design with closed-loop real-time fMRI. 320-334 2016 129 NeuroImage https://doi.org/10.1016/j.neuroimage.2016.01.032 https://www.wikidata.org/entity/Q27306682 db/journals/neuroimage/neuroimage129.html#LorenzMVAFML16

Romy Lorenz Ricardo Pio Monti Adam Hampshire Yury Koush Christoforos Anagnostopoulos Aldo A. Faisal David J. Sharp Giovanni Montana Robert Leech Inês R. Violante Towards tailoring non-invasive brain stimulation using real-time fMRI and Bayesian optimization. 1-4 2016 PRNI https://doi.org/10.1109/PRNI.2016.7552338 https://www.wikidata.org/entity/Q57744831 conf/prni/2016 db/conf/prni/prni2016.html#LorenzMHKAFSMLV16 Ricardo Pio Monti Romy Lorenz Robert Leech Christoforos Anagnostopoulos Giovanni Montana Text-mining the neurosynth corpus using deep boltzmann machines. 1-4 2016 PRNI https://doi.org/10.1109/PRNI.2016.7552329 https://www.wikidata.org/entity/Q57744829 conf/prni/2016 db/conf/prni/prni2016.html#MontiLLAM16

Ricardo Pio Monti Romy Lorenz Robert Leech Christoforos Anagnostopoulos Giovanni Montana Text-mining the NeuroSynth corpus using Deep Boltzmann Machines. 2016 abs/1605.00223 CoRR http://arxiv.org/abs/1605.00223 db/journals/corr/corr1605.html#MontiLLAM16

Ricardo Pio Monti Christoforos Anagnostopoulos Giovanni Montana A framework for adaptive regularization in streaming Lasso models. 2016 abs/1610.09127 CoRR http://arxiv.org/abs/1610.09127 db/journals/corr/corr1610.html#MontiAM16

Ricardo Pio Monti Romy Lorenz Peter Hellyer Robert Leech Christoforos Anagnostopoulos Giovanni Montana Graph Embeddings of Dynamic Functional Connectivity Reveal Discriminative Patterns of Task Engagement in HCP Data. 1-4 2015 PRNI https://doi.org/10.1109/PRNI.2015.21 https://doi.ieeecomputersociety.org/10.1109/PRNI.2015.21 https://www.wikidata.org/entity/Q57744837 conf/prni/2015 db/conf/prni/prni2015.html#MontiLHLAM15

Lewis Percival Gordon Evans Niall M. Adams Christoforos Anagnostopoulos Estimating Optimal Active Learning via Model Retraining Improvement. 2015 abs/1502.01664 CoRR http://arxiv.org/abs/1502.01664 db/journals/corr/corr1502.html#EvansAA15

Ricardo Pio Monti Peter Hellyer David J. Sharp Robert Leech Christoforos Anagnostopoulos Giovanni Montana Estimating time-varying brain connectivity networks from functional MRI time series. 427-443 2014 103 NeuroImage https://doi.org/10.1016/j.neuroimage.2014.07.033 https://www.wikidata.org/entity/Q45798515 db/journals/neuroimage/neuroimage103.html#MontiHSLAM14

David J. Hand Christoforos Anagnostopoulos A better Beta for the H measure of classification performance. 41-46 2014 40 Pattern Recognit. Lett. https://doi.org/10.1016/j.patrec.2013.12.011 db/journals/prl/prl40.html#HandA14

Lewis Percival Gordon Evans Niall M. Adams Christoforos Anagnostopoulos Targeting Optimal Active Learning via Example Quality. 2014 abs/1407.8042 CoRR http://arxiv.org/abs/1407.8042 db/journals/corr/corr1407.html#EvansAA14

Lewis Percival Gordon Evans Niall M. Adams Christoforos Anagnostopoulos When does Active Learning Work? 2014 abs/1408.1319 CoRR http://arxiv.org/abs/1408.1319 db/journals/corr/corr1408.html#EvansAA14a

Christoforos Anagnostopoulos Robert B. Gramacy Information-Theoretic Data Discarding for Dynamic Trees on Data Streams. 5510-5535 2013 15 Entropy 12 https://doi.org/10.3390/e15125510 db/journals/entropy/entropy15.html#AnagnostopoulosG13

David J. Hand Christoforos Anagnostopoulos When is the area under the receiver operating characteristic curve an appropriate measure of classifier performance? 492-495 2013 34 Pattern Recognit. Lett. 5 https://doi.org/10.1016/j.patrec.2012.12.004 db/journals/prl/prl34.html#HandA13

Lewis Percival Gordon Evans Niall M. Adams Christoforos Anagnostopoulos When Does Active Learning Work? 174-185 2013 IDA https://doi.org/10.1007/978-3-642-41398-8_16 conf/ida/2013 db/conf/ida/ida2013.html#EvansAA13

Christoforos Anagnostopoulos Dimitris K. Tasoulis Niall M. Adams Nicos G. Pavlidis David J. Hand Online linear and quadratic discriminant analysis with adaptive forgetting for streaming classification. 139-166 2012 5 Stat. Anal. Data Min. 2 https://doi.org/10.1002/sam.10151 db/journals/sadm/sadm5.html#AnagnostopoulosTAPH12

David J. Hand Christoforos Anagnostopoulos A better Beta for the H measure of classification performance http://arxiv.org/abs/1202.2564 2012 CoRR abs/1202.2564 db/journals/corr/corr1202.html#abs-1202-2564

Christoforos Anagnostopoulos Niall M. Adams David J. Hand Streaming Covariance Selection with Applications to Adaptive Querying in Sensor Networks. 1401-1414 2010 53 Comput. J. 9 https://doi.org/10.1093/comjnl/bxp123 db/journals/cj/cj53.html#AnagnostopoulosAH10

Niall M. Adams Dimitris K. Tasoulis Christoforos Anagnostopoulos David J. Hand Temporally-Adaptive Linear Classification for Handling Population Drift in Credit Scoring. 167-176 2010 COMPSTAT https://doi.org/10.1007/978-3-7908-2604-3_15 conf/compstat/2010 db/conf/compstat/compstat2010.html#AdamsTAH10

Christoforos Anagnostopoulos Dimitris K. Tasoulis Niall M. Adams David J. Hand Temporally adaptive estimation of logistic classifiers on data streams. 243-261 2009 3 Adv. Data Anal. Classif. 3 https://doi.org/10.1007/s11634-009-0051-x db/journals/adac/adac3.html#AnagnostopoulosTAH09

Christoforos Anagnostopoulos Dimitris K. Tasoulis David J. Hand Niall M. Adams Online optimization for variable selection in data streams. 132-136 2008 ECAI https://doi.org/10.3233/978-1-58603-891-5-132 conf/ecai/2008 db/conf/ecai/ecai2008.html#AnagnostopoulosTHA08 Christoforos Anagnostopoulos Niall M. Adams David J. Hand Deciding what to observe next: adaptive variable selection for regression in multivariate data streams. 961-965 2008 SAC https://doi.org/10.1145/1363686.1363909 conf/sac/2008 db/conf/sac/sac2008.html#AnagnostopoulosAH08 Christoforos Anagnostopoulos Niall M. Adams Simulating Dynamic Covariance Structures for Testing the Adaptive Behavior of Variable Selection Algorithms. 52-57 2008 UKSim https://doi.org/10.1109/UKSIM.2008.92 https://doi.ieeecomputersociety.org/10.1109/UKSIM.2008.92 conf/uksim/2008 db/conf/uksim/uksim2008.html#AnagnostopoulosA08 Niall M. Adams Lewis Percival Gordon Evans A. Aldo FaisalAldo A. Faisal Robert B. Gramacy Adam Hampshire David J. Hand Peter Hellyer Yury Koush Robert Leech Romy Lorenz Giovanni Montana Ricardo Pio Monti Nicos G. Pavlidis David J. Sharp Dimitris K. Tasoulis Inês R. Violante