Matches in SemOpenAlex for { <https://semopenalex.org/work/W2143375172> ?p ?o ?g. }
Showing items 1 to 89 of
89
with 100 items per page.
- W2143375172 endingPage "81" @default.
- W2143375172 startingPage "65" @default.
- W2143375172 abstract "Many regression schemes deliver a point estimate only, but often it is useful or even essential to quantify the uncertainty inherent in a prediction. If a conditional density estimate is available, then prediction intervals can be derived from it. In this paper we compare three techniques for computing conditional density estimates using a class probability estimator, where this estimator is applied to the discretized target variable and used to derive instance weights for an underlying univariate density estimator; this yields a conditional density estimate. The three density estimators we compare are: a histogram estimator that has been used previously in this context, a normal density estimator, and a kernel estimator. In our experiments, the latter two deliver better performance, both in terms of cross-validated log-likelihood and in terms of quality of the resulting prediction intervals. The empirical coverage of the intervals is close to the desired confidence level in most cases. We also include results for point estimation, as well as a comparison to Gaussian process regression and nonparametric quantile estimation." @default.
- W2143375172 created "2016-06-24" @default.
- W2143375172 creator A5027519870 @default.
- W2143375172 creator A5059992863 @default.
- W2143375172 date "2009-01-01" @default.
- W2143375172 modified "2023-10-17" @default.
- W2143375172 title "Conditional Density Estimation with Class Probability Estimators" @default.
- W2143375172 cites W1568654892 @default.
- W2143375172 cites W1991502340 @default.
- W2143375172 cites W1997855593 @default.
- W2143375172 cites W2024228246 @default.
- W2143375172 cites W2063241008 @default.
- W2143375172 cites W2069257437 @default.
- W2143375172 cites W2094711828 @default.
- W2143375172 cites W2114618665 @default.
- W2143375172 cites W2120199131 @default.
- W2143375172 cites W2125336244 @default.
- W2143375172 cites W4214746649 @default.
- W2143375172 doi "https://doi.org/10.1007/978-3-642-05224-8_7" @default.
- W2143375172 hasPublicationYear "2009" @default.
- W2143375172 type Work @default.
- W2143375172 sameAs 2143375172 @default.
- W2143375172 citedByCount "26" @default.
- W2143375172 countsByYear W21433751722013 @default.
- W2143375172 countsByYear W21433751722014 @default.
- W2143375172 countsByYear W21433751722015 @default.
- W2143375172 countsByYear W21433751722016 @default.
- W2143375172 countsByYear W21433751722017 @default.
- W2143375172 countsByYear W21433751722018 @default.
- W2143375172 countsByYear W21433751722020 @default.
- W2143375172 countsByYear W21433751722021 @default.
- W2143375172 countsByYear W21433751722023 @default.
- W2143375172 crossrefType "book-chapter" @default.
- W2143375172 hasAuthorship W2143375172A5027519870 @default.
- W2143375172 hasAuthorship W2143375172A5059992863 @default.
- W2143375172 hasBestOaLocation W21433751722 @default.
- W2143375172 hasConcept C105795698 @default.
- W2143375172 hasConcept C115961682 @default.
- W2143375172 hasConcept C118671147 @default.
- W2143375172 hasConcept C122280245 @default.
- W2143375172 hasConcept C12267149 @default.
- W2143375172 hasConcept C154945302 @default.
- W2143375172 hasConcept C185429906 @default.
- W2143375172 hasConcept C189508267 @default.
- W2143375172 hasConcept C195699287 @default.
- W2143375172 hasConcept C33923547 @default.
- W2143375172 hasConcept C41008148 @default.
- W2143375172 hasConcept C41426520 @default.
- W2143375172 hasConcept C43555835 @default.
- W2143375172 hasConcept C53533937 @default.
- W2143375172 hasConcept C71134354 @default.
- W2143375172 hasConcept C84894716 @default.
- W2143375172 hasConceptScore W2143375172C105795698 @default.
- W2143375172 hasConceptScore W2143375172C115961682 @default.
- W2143375172 hasConceptScore W2143375172C118671147 @default.
- W2143375172 hasConceptScore W2143375172C122280245 @default.
- W2143375172 hasConceptScore W2143375172C12267149 @default.
- W2143375172 hasConceptScore W2143375172C154945302 @default.
- W2143375172 hasConceptScore W2143375172C185429906 @default.
- W2143375172 hasConceptScore W2143375172C189508267 @default.
- W2143375172 hasConceptScore W2143375172C195699287 @default.
- W2143375172 hasConceptScore W2143375172C33923547 @default.
- W2143375172 hasConceptScore W2143375172C41008148 @default.
- W2143375172 hasConceptScore W2143375172C41426520 @default.
- W2143375172 hasConceptScore W2143375172C43555835 @default.
- W2143375172 hasConceptScore W2143375172C53533937 @default.
- W2143375172 hasConceptScore W2143375172C71134354 @default.
- W2143375172 hasConceptScore W2143375172C84894716 @default.
- W2143375172 hasLocation W21433751721 @default.
- W2143375172 hasLocation W21433751722 @default.
- W2143375172 hasLocation W21433751723 @default.
- W2143375172 hasOpenAccess W2143375172 @default.
- W2143375172 hasPrimaryLocation W21433751721 @default.
- W2143375172 hasRelatedWork W1586412939 @default.
- W2143375172 hasRelatedWork W2144201579 @default.
- W2143375172 hasRelatedWork W2355371556 @default.
- W2143375172 hasRelatedWork W2945453291 @default.
- W2143375172 hasRelatedWork W3038120911 @default.
- W2143375172 hasRelatedWork W3123419490 @default.
- W2143375172 hasRelatedWork W3212687977 @default.
- W2143375172 hasRelatedWork W4239457139 @default.
- W2143375172 hasRelatedWork W4386285810 @default.
- W2143375172 hasRelatedWork W1834385407 @default.
- W2143375172 isParatext "false" @default.
- W2143375172 isRetracted "false" @default.
- W2143375172 magId "2143375172" @default.
- W2143375172 workType "book-chapter" @default.