Synoniemen & Informatie over | Engels woord CROSS-VALIDATION
CROSS-VALIDATION
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(Nederlands) Wiktionary
(Nederlands) Wikipedia
(Engels) Wiktionary
(Engels) Google Answers
(Engels) Britannica
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Voorbeelden van het gebruik van CROSS-VALIDATION in een zin
- internal validation or cross-validation (actually, while extracting data, cross validation is a measure of model robustness, the more a model is robust (higher q2) the less data extraction perturb the original model);.
- As the process was repeated in subsequent sessions, more and more software components were added so that the experimenter had less and less to do during each session until asymptotic was reached on phrase/word dictionary growth and the experimenter could "go get a cup of coffee" during the session (which at this point was a cross-validation of the final system's unattended performance).
- Jackknifing (jackknife cross-validation), is used in statistical inference to estimate the bias and standard error (variance) of a statistic, when a random sample of observations is used to calculate it.
- In statistics, the jackknife (jackknife cross-validation) is a cross-validation technique and, therefore, a form of resampling.
- Backtesting is a type of retrodiction, and a special type of cross-validation applied to previous time period(s).
- The basic LMT induction algorithm uses cross-validation to find a number of LogitBoost iterations that does not overfit the training data.
- He has also made numerous novel contributions to nonparametric statistics (obtaining the surprising result that cross-validation does not suffer from the curse of dimensionality for consistent estimation of the embedding dimension of a dynamical system), Markov chain modelling (with application to weather data), reliability, non-stationary time series analysis (in both the frequency domain and the time domain) and wavelets.
- Grid search then trains an SVM with each pair (C, γ) in the Cartesian product of these two sets and evaluates their performance on a held-out validation set (or by internal cross-validation on the training set, in which case multiple SVMs are trained per pair).
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