Results 21 to 30 of about 1,327,683 (276)
Local Cross-validation for Spectrum Bandwidth Choice [PDF]
, 2000 We investigate an automatic method of determining a local bandwidth for non-parametric kernel spectral density estimates at a single frequency. This procedure is a modification of a cross-validation technique for global bandwidth choices, avoiding the ...
Velasco, Carlos
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, 2017 This text is a survey on cross-validation. We define all classical cross-validation procedures, and we study their properties for two different goals: estimating the risk of a given estimator, and selecting the best estimator among a given family. For the risk estimation problem, we compute the bias (which can also be corrected) and the variance of ...
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Consensus Features Nested Cross-Validation [PDF]
Bioinformatics, 2020 AbstractMotivationFeature selection can improve the accuracy of machine learning models, but appropriate steps must be taken to avoid overfitting. Nested cross-validation (nCV) is a common approach that chooses the classification model and features to represent a given outer fold based on features that give the maximum inner-fold accuracy. Differential
Parvandeh, Saeid +3 more
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Potential Skill Map of Predictors Applied to the Seasonal Forecast of Summer Rainfall in China
应用气象学报, 2020 Anomalous summer rainfall in China is affected by many factors, whose complex interaction restricts the predictability of Chinese summer rainfall (CSR).
Liu Boqi, Zhu Congwen
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Slope heuristics and V-Fold model selection in heteroscedastic regression using strongly localized bases [PDF]
, 2016 We investigate the optimality for model selection of the so-called slope heuristics, $V$-fold cross-validation and $V$-fold penalization in a heteroscedastic with random design regression context.
Navarro, Fabien, Saumard, Adrien
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Human activity recognition making use of long short-term memory techniques [PDF]
, 2019 The optimisation and validation of a classifiers performance when applied to real world problems is not always effectively shown. In much of the literature describing the application of artificial neural network architectures to Human Activity ...
Shenfield, Alex, Wainwright, Richard
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Bandwidth Selection in Nonparametric Regression with Large Sample Size
Proceedings, 2018 In the context of nonparametric regression estimation, the behaviour of kernel methods such as the Nadaraya-Watson or local linear estimators is heavily influenced by the value of the bandwidth parameter, which determines the trade-off between bias and ...
Daniel Barreiro-Ures +2 more
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Improving the accuracy of classification algorithms for inductive learning rules using wrapper methods [PDF]
Tehnika, 2015 In this paper we investigate the problem of the accuracy of classifier using wrapper methods. For the purposes of classification is used a large number of algorithms: IBK, Naïve Bayes, SVM, J48 decision tree and RBF networks.
Novaković Jasmina Đ.
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A comparative evaluation of nonlinear dynamics methods for time series prediction [PDF]
, 2009 A key problem in time series prediction using autoregressive models is to fix the model order, namely the number of past samples required to model the time series adequately. The estimation of the model order using cross-validation may be a long process.
Camastra, F., Filippone, M.
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Efficient algorithms for decision tree cross-validation
, 2001 Cross-validation is a useful and generally applicable technique often employed in machine learning, including decision tree induction. An important disadvantage of straightforward implementation of the technique is its computational overhead.
Blockeel, Hendrik, Struyf, Jan
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