• Title, Summary, Keyword: cross-validation

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Candidate Points and Representative Cross-Validation Approach for Sequential Sampling (후보점과 대표점 교차검증에 의한 순차적 실험계획)

  • Kim, Seung-Won;Jung, Jae-Jun;Lee, Tae-Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.31 no.1
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    • pp.55-61
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    • 2007
  • Recently simulation model becomes an essential tool for analysis and design of a system but it is often expensive and time consuming as it becomes complicate to achieve reliable results. Therefore, high-fidelity simulation model needs to be replaced by an approximate model, the so-called metamodel. Metamodeling techniques include 3 components of sampling, metamodel and validation. Cross-validation approach has been proposed to provide sequnatially new sample point based on cross-validation error but it is very expensive because cross-validation must be evaluated at each stage. To enhance the cross-validation of metamodel, sequential sampling method using candidate points and representative cross-validation is proposed in this paper. The candidate and representative cross-validation approach of sequential sampling is illustrated for two-dimensional domain. To verify the performance of the suggested sampling technique, we compare the accuracy of the metamodels for various mathematical functions with that obtained by conventional sequential sampling strategies such as maximum distance, mean squared error, and maximum entropy sequential samplings. Through this research we team that the proposed approach is computationally inexpensive and provides good prediction performance.

Bandwidth selections based on cross-validation for estimation of a discontinuity point in density (교차타당성을 이용한 확률밀도함수의 불연속점 추정의 띠폭 선택)

  • Huh, Jib
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.4
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    • pp.765-775
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    • 2012
  • The cross-validation is a popular method to select bandwidth in all types of kernel estimation. The maximum likelihood cross-validation, the least squares cross-validation and biased cross-validation have been proposed for bandwidth selection in kernel density estimation. In the case that the probability density function has a discontinuity point, Huh (2012) proposed a method of bandwidth selection using the maximum likelihood cross-validation. In this paper, two forms of cross-validation with the one-sided kernel function are proposed for bandwidth selection to estimate the location and jump size of the discontinuity point of density. These methods are motivated by the least squares cross-validation and the biased cross-validation. By simulated examples, the finite sample performances of two proposed methods with the one of Huh (2012) are compared.

Smoothing Parameter Selection Using Multifold Cross-Validation in Smoothing Spline Regressions

  • Hong, Changkon;Kim, Choongrak;Yoon, Misuk
    • Communications for Statistical Applications and Methods
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    • v.5 no.2
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    • pp.277-285
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    • 1998
  • The smoothing parameter $\lambda$ in smoothing spline regression is usually selected by minimizing cross-validation (CV) or generalized cross-validation (GCV). But, simple CV or GCV is poor candidate for estimating prediction error. We defined MGCV (Multifold Generalized Cross-validation) as a criterion for selecting smoothing parameter in smoothing spline regression. This is a version of cross-validation using $leave-\kappa-out$ method. Some numerical results comparing MGCV and GCV are done.

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CROSS- VALIDATION OF LANDSLIDE SUSCEPTIBILITY MAPPING IN KOREA

  • LEE SARO
    • Proceedings of the KSRS Conference
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    • pp.291-293
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    • 2004
  • The aim of this study was to cross-validate a spatial probabilistic model of landslide likelihood ratios at Boun, Janghung and Yongin, in Korea, using a Geographic Information System (GIS). Landslide locations within the study areas were identified by interpreting aerial photographs, satellite images and field surveys. Maps of the topography, soil type, forest cover, lineaments and land cover were constructed from the spatial data sets. The 14 factors that influence landslide occurrence were extracted from the database and the likelihood ratio of each factor was computed. 'Landslide susceptibility maps were drawn for these three areas using likelihood ratios derived not only from the data for that area but also using the likelihood ratios calculated from each of the other two areas (nine maps in all) as a cross-check of the validity of the method For validation and cross-validation, the results of the analyses were compared, in each study area, with actual landslide locations. The validation and cross-validation of the results showed satisfactory agreement between the susceptibility map and the existing landslide locations.

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ROBUST CROSS VALIDATIONS IN RIDGE REGRESSION

  • Jung, Kang-Mo
    • Journal of applied mathematics & informatics
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    • v.27 no.3_4
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    • pp.903-908
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    • 2009
  • The shrink parameter in ridge regression may be contaminated by outlying points. We propose robust cross validation scores in ridge regression instead of classical cross validation. We use robust location estimators such as median, least trimmed squares, absolute mean for robust cross validation scores. The robust scores have global robustness. Simulations are performed to show the effectiveness of the proposed estimators.

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Cross-Validation method for Science and Technology Research Paper considering Interdisciplinary Approach (다학제적 접근을 고려한 과학기술논문 상호검증 방법)

  • Han, Young-shin
    • Journal of Engineering Education Research
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    • v.18 no.5
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    • pp.3-10
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    • 2015
  • Researchers in science and technology has broadened the scope of research in order to solve complex problems, academic exchange has also been actively carried out. If the paper which is a mean of interdisciplinary approach has a limited term and the formula, it can act as barriers to access for many researchers in various fields. This paper proposes a cross-validation method for eliminating documentary barriers based on discrete event system formalism. We expect that our proposed method will improve a cross-validation considering researchers in another fields.

SVM Load Forecasting using Cross-Validation (교차검증을 이용한 SVM 전력수요예측)

  • Jo, Nam-Hoon
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.55 no.11
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    • pp.485-491
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    • 2006
  • In this paper, we study the problem of model selection for Support Vector Machine(SVM) predictor for short-term load forecasting. The model selection amounts to tuning SVM parameters, such as the cost coefficient C and kernel parameters and so on, in order to maximize the prediction performance of SVM. We propose that Cross-Validation method can be used as a model selection algorithm for SVM-based load forecasting technique. Through the various experiments on several data sets, we found that the difference between the prediction error of SVM using Cross-Validation and that of ideal SVM is less than 5%. This shows that SVM parameters for load forecasting can be efficiently tuned by using Cross-Validation.

Method Development and Cross Validation of Analysis of Hydroxylated Polycyclic Aromatic Hydrocarbons (OH-PAHs) in Human Urine (소변 중 다환방향족탄화수소 대사체의 분석법 확립 및 교차분석)

  • Park, Na-Youn;Jeon, Jung-Dae;Koo, Hyeryeong;Kim, Jung Hoan;Lee, Eun-Hee;Lee, Kyungmu;Mun, Cheoljin;Kho, Younglim
    • Journal of Environmental Health Sciences
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    • v.41 no.5
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    • pp.358-367
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    • 2015
  • Objectives: This study was performed to evaluate the analytical method for PAH metabolites in human urine using enzyme hydrolysis and solid-phase extraction coupled with LC-(ESI)-MS/MS technique. Methods: We employed HPLC tandem mass spectrometry techniques with appropriate pre-treatment for analysis of 16 OH-PAHs in human urine. Samples were hydrolysis by ${\beta}$-flucuronidase/Aryl sulfatase, and target compounds were extracted by solid-phase extraction with a strata-x cartridge. Cross-validation was performed between Eulji University and Green Cross laboratories with 200 human urine samples. Results: The accuracies were between 90.3% and 118.8%, and precisions (relative standard deviations) were lower than 10%. The linearity obtained was satisfying for the 16 OH-PAH compounds, with a coefficient of determination ($r^2$) higher than 0.99. The results of cross-validation at the two organizations were compared by ICC (interclass correlation coefficient) values. The cross-validation results were excellent or good for all compounds. Conclusion: An analytical method was validated for low nanogram levels of 16 OH-PAHs in human urine. Also, satisfying results were obtained for method validation such as accuracy, precision and ICC of cross-validation.

Improvement of Neural Network Performance for Estimating Defect Size of Steam Generator Tube using Multifold Cross-Validation (다중겹 교차검증 기법을 이용한 증기세관 결함크기 예측을 위한 신경회로망 성능 향상)

  • Kim, Nam-Jin;Jee, Su-Jung;Jo, Nam-Hoon
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.26 no.9
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    • pp.73-79
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    • 2012
  • In this paper, we study on how to determine the number of hidden layer neurons in neural network for predicting defect size of steam generator tube. It was reported in the literature that the number of hidden layer neurons can be efficiently determined with the help of cross-validation. Although the cross-validation provides decent estimation performance in most cases, the performance depends on the selection of validation set and rather poor performance may be led to in some cases. In order to avoid such a problem, we propose to use multifold cross-validation. Through the simulation study, it is shown that the estimation performance of defect width (defect depth, respectively) attains 94% (99.4%, respectively) of the best performance achievable among the considered neuron numbers.

Cross-cultural Validation of Instruments Measuring Health Beliefs about Colorectal Cancer Screening among Korean Americans

  • Lee, Shin-Young;Lee, Eunice E.
    • Journal of Korean Academy of Nursing
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    • v.45 no.1
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    • pp.129-138
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    • 2015
  • Purpose: The purpose of this study was to report the instrument modification and validation processes to make existing health belief model scales culturally appropriate for Korean Americans (KAs) regarding colorectal cancer (CRC) screening utilization. Methods: Instrument translation, individual interviews using cognitive interviewing, and expert reviews were conducted during the instrument modification phase, and a pilot test and a cross-sectional survey were conducted during the instrument validation phase. Data analyses of the cross-sectional survey included internal consistency and construct validity using exploratory and confirmatory factor analysis. Results: The main issues identified during the instrument modification phase were (a) cultural and linguistic translation issues and (b) newly developed items reflecting Korean cultural barriers. Cross-sectional survey analyses during the instrument validation phase revealed that all scales demonstrate good internal consistency reliability (Cronbach's alpha=.72~.88). Exploratory factor analysis showed that susceptibility and severity loaded on the same factor, which may indicate a threat variable. Items with low factor loadings in the confirmatory factor analysis may relate to (a) lack of knowledge about fecal occult blood testing and (b) multiple dimensions of the subscales. Conclusion: Methodological, sequential processes of instrument modification and validation, including translation, individual interviews, expert reviews, pilot testing and a cross-sectional survey, were provided in this study. The findings indicate that existing instruments need to be examined for CRC screening research involving KAs.