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Cognition, ISSN 0010-0277, 2011, Volume 118, Issue 1, pp. 2 - 16
In this paper we propose that the conventional dichotomy between exemplar-based and prototype-based models of concept learning is helpfully viewed as an... 
Concept learning | Bias/variance | Complexity | SIMPLICITY PRINCIPLE | DENSITY-ESTIMATION | CLASSIFICATION | MODEL | IDENTIFICATION | PSYCHOLOGY, EXPERIMENTAL | PROTOTYPES | HUMAN CATEGORIZATION | SIMILARITY | RULES | EXEMPLAR | Models | Evaluation Methods | Measures (Individuals) | Statistical Analysis | Bias | Analysis | Cognition
Journal Article
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, ISSN 1939-1404, 04/2014, Volume 7, Issue 4, pp. 1089 - 1102
Journal Article
Talanta, ISSN 0039-9140, 07/2015, Volume 139, pp. 40 - 49
Different measures of selectivity are in use for single channel and multichannel linear analytical measurements, respectively. It is important to understand... 
Error inflation | Selectivity | Bias variance tradeoff | Multivariate | Interference | ANALYTICAL FIGURES | CALIBRATION | CHEMISTRY, ANALYTICAL | MERIT | SENSITIVITY | FRAMEWORK | UNIVARIATE
Journal Article
ICES Journal of Marine Science, ISSN 1054-3139, 01/2019, Volume 76, Issue 1, pp. 255 - 267
Abstract Quantifying effects of fishing on non-targeted (bycatch) species is an important management and conservation issue. Bycatch estimates are typically... 
bias-variance tradeoff | fishing effort | GAM (generalized additive model) | random forest | US west coast groundfish fishery | ratio estimator | FISHERY | ABUNDANCE | STRATEGIES | bycatch estimation | RATES | FISHERIES | STANDARDIZING CATCH | MARINE & FRESHWATER BIOLOGY | OCEANOGRAPHY | discards | ERROR | spatial model
Journal Article
Computational Intelligence, ISSN 0824-7935, 02/2019, Volume 35, Issue 1, pp. 184 - 203
Ensemble learning is a popular classification method where many individual simple learners contribute to a final prediction. Constructing an ensemble of... 
bias‐variance tradeoff | ensemble learning | classification | bias-variance tradeoff | NEURAL-NETWORKS | MULTICLASS | BINARY | MODEL | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Bagging | Parameters | Classification
Journal Article
Condor, ISSN 0010-5422, 11/2018, Volume 120, Issue 4, pp. 765 - 786
We used conventional and finite mixture removal models with and without time-varying covariates to evaluate availability given presence for 152 bird species... 
bias-variance tradeoff | boreal birds | population size | abundance | detectability | DENSITY | PROBABILITY | CLIMATE-CHANGE | SCIENCE | ORNITHOLOGY | PHENOLOGY | INDEXES | Availability | Parameter estimation | Sample size | Bias | Estimation | Population number | Birds | Polls & surveys | Variance | Surveys | Heterogeneity | Animal behavior | Models | Mathematical models
Journal Article
2010, Synthesis lectures on artificial intelligence and machine learning, ISBN 1608454932, Volume 9.
Web Resource
Organizational Research Methods, ISSN 1094-4281, 7/2018, Volume 21, Issue 3, pp. 689 - 732
Journal Article
American Journal of Epidemiology, ISSN 0002-9262, 02/2018, Volume 187, Issue 2, pp. 366 - 377
Journal Article
The American Statistician, ISSN 0003-1305, 01/2014, Volume 68, Issue 1, pp. 17 - 29
Simpson's Paradox is really a Simple Paradox if one at all. Peeling away the paradox is as easy (or hard) as avoiding a comparison of apples and oranges, a... 
Bias-variance tradeoff | Principal stratification | STATISTICS & PROBABILITY | CAUSAL INFERENCE | Variables | Estimating techniques | Causality | Comparative analysis
Journal Article