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Selection: with tag overfitting [7 articles] 


Rules of thumb for judging ecological theories

Trends in Ecology & Evolution, Vol. 19, No. 3. (March 2004), pp. 121-126,


An impressive fit to historical data suggests to biologists that a given ecological model is highly valid. Models often achieve this fit at the expense of exaggerated complexity that is not justified by empirical evidence. Because overfitted theories complement the traditional assumption that ecology is `messy', they generally remain unquestioned. Using predation theory as an example, we suggest that a fit-driven appraisal of model value is commonly misdirected; although fit to historical data can be important, the simplicity and generality of ...


(INRMM-MiD internal record) List of keywords of the INRMM meta-information database - part 23

(February 2014)
Keywords: inrmm-list-of-tags   nolina-recurvata   non-array-oriented   non-equilibrium   non-linearity   non-semantic-software-errors   non-stationarity   non-wood-products   nonadditive-measures   nonideal-neurons   nonlinear-correlation   nonlinear-response-to-bioclimatic-predictors   nonmarket-impacts   nonsteady-flame-convection   north-africa   north-america   northern-europe   northern-hemisphere   norway   not-automatic-workflow   notation   notation-as-a-tool-of-thought   nothofagus-cunninghamii   nothofagus-glauca   nothofagus-nervosa   nothofagus-procera   nothofagus-pumilio   nothofagus-spp   notholithocarpus-densiflorus   nothotsuga-spp   nreap-2020   nuclear-disasters   numerical-analysis   numpy   nurse-species   nut-producing-plants   nutrient-gradient   nutrient-recommendations   nutrient-rich-soil   nutrients   nutritional-composition   nyssa-spp   nyssa-sylvatica   oak-decline   oak-hornbeam-forest   oak-shake   object-oriented-programming   occam-razor   ocean-acidification   ocean-circulation   oceans   ochroma-pyramidale   oenothera-spp   off-site-effects   ogc   olea-europaea   olea-spp   oleoresin   olive-decline   olive-oil   ombrotrophic   on-site-effects   ononis-fruticosa   ontologies   open-access   open-access-embargo   open-data   open-field   open-loop-control   open-science   open-source   opengis   openlayers   openstreetmap   operational-research   operophtera-antiqua   operophtera-brumata   ophiostoma-novo-ulmi   ophiostoma-spp   ophiostoma-ulmi   opportunistic-plant-pests   optimization   opuntia-amyclaea   opuntia-ficus-indica   oregon   organic-carbon   organic-material   ornamental-plant   ornamental-trees   orthotomicus-laricis   ostrya-carpinifolia   ostrya-spp   ostryopsis-spp   otiorhynchus-scaber   outbreak   outdated-yield-tables   outputs-vs-outcomes   overexploited-fish-stocks   overfitting  


List of indexed keywords within the transdisciplinary set of domains which relate to the Integrated Natural Resources Modelling and Management (INRMM). In particular, the list of keywords maps the semantic tags in the INRMM Meta-information Database (INRMM-MiD). [\n] The INRMM-MiD records providing this list are accessible by the special tag: inrmm-list-of-tags ( ). ...


Accurately measuring model prediction error



When assessing the quality of a model, being able to accurately measure its prediction error is of key importance. Often, however, techniques of measuring error are used that give grossly misleading results. This can lead to the phenomenon of over-fitting where a model may fit the training data very well, but will do a poor job of predicting results for new data not used in model training. Here is an overview of methods to accurately measure model prediction error. ...

Visual summary


Understanding the bias-variance tradeoff



When we discuss prediction models, prediction errors can be decomposed into two main subcomponents we care about: error due to "bias" and error due to "variance". There is a tradeoff between a model's ability to minimize bias and variance. Understanding these two types of error can help us diagnose model results and avoid the mistake of over- or under-fitting. ...

Visual summary


The reusable holdout: preserving validity in adaptive data analysis

Science, Vol. 349, No. 6248. (07 August 2015), pp. 636-638,


[Editor's summary: Testing hypotheses privately] Large data sets offer a vast scope for testing already-formulated ideas and exploring new ones. Unfortunately, researchers who attempt to do both on the same data set run the risk of making false discoveries, even when testing and exploration are carried out on distinct subsets of data. Based on ideas drawn from differential privacy, Dwork et al. now provide a theoretical solution. Ideas are tested against aggregate information, whereas individual data set components remain confidential. Preserving that ...


Spatial prediction models for landslide hazards: review, comparison and evaluation

Natural Hazards and Earth System Science, Vol. 5, No. 6. (7 November 2005), pp. 853-862,


The predictive power of logistic regression, support vector machines and bootstrap-aggregated classification trees (bagging, double-bagging) is compared using misclassification error rates on independent test data sets. Based on a resampling approach that takes into account spatial autocorrelation, error rates for predicting "present" and "future" landslides are estimated within and outside the training area. In a case study from the Ecuadorian Andes, logistic regression with stepwise backward variable selection yields lowest error rates and demonstrates the best generalization capabilities. The evaluation outside ...


How Does Climate Change Affect Biodiversity?

Science, Vol. 313, No. 5792. (08 September 2006), pp. 1396-1397,


The most recent and complex bioclimate models excel at describing species' current distributions. Yet, it is unclear which models will best predict how climate change will affect their future distributions. ...

This page of the database may be cited as:
Integrated Natural Resources Modelling and Management - Meta-information Database.

Publication metadata

Bibtex, RIS, RSS/XML feed, Json, Dublin Core

Meta-information Database (INRMM-MiD).
This database integrates a dedicated meta-information database in CiteULike (the CiteULike INRMM Group) with the meta-information available in Google Scholar, CrossRef and DataCite. The Altmetric database with Article-Level Metrics is also harvested. Part of the provided semantic content (machine-readable) is made even human-readable thanks to the DCMI Dublin Core viewer. Digital preservation of the meta-information indexed within the INRMM-MiD publication records is implemented thanks to the Internet Archive.
The library of INRMM related pubblications may be quickly accessed with the following links.
Search within the whole INRMM meta-information database:
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Full-text and abstracts of the publications indexed by the INRMM meta-information database are copyrighted by the respective publishers/authors. They are subject to all applicable copyright protection. The conditions of use of each indexed publication is defined by its copyright owner. Please, be aware that the indexed meta-information entirely relies on voluntary work and constitutes a quite incomplete and not homogeneous work-in-progress.
INRMM-MiD was experimentally established by the Maieutike Research Initiative in 2008 and then improved with the help of several volunteers (with a major technical upgrade in 2011). This new integrated interface is operational since 2014.