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Cross-Validation Visualized: A Narrative Guide to Advanced Methods
Machine Learning and Knowledge ExtractionThis study delves into the multifaceted nature of cross-validation (CV) techniques in machine learning model evaluation and selection, underscoring the challenge of choosing the most appropriate method due to the plethora of available variants.
Johannes Allgaier, Rüdiger Pryss
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PENAKSIRAN FUNGSI DENSITAS TIPE KERNEL DENGAN METODE CROSS-VALIDATION (C-V)
Barekeng, 2007 The choice of the bandwidth h is the main problem of kernel density function. In some situations it might be quite useful to have a set of retes corresponding to different bandwidth.It is necessary to agree which bandwidth is an appropriate one.
Mozart W. Talakua
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Cells, 2019 Identifying the interactions between disease and microRNA (miRNA) can accelerate drugs development, individualized diagnosis, and treatment for various human diseases. However, experimental methods are time-consuming and costly.
Chunyan Li +4 more
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Geostatistical-based geophysical model of electrical resistivity and chargeability data applied to image copper mineralization in the Ghalandar deposit, Iran [PDF]
International Journal of Mining and Geo-Engineering, 2020 This research aims to construct 3D geophysical models of electrical resistivity and induced polarization by interpolating 2D inverted physical models through the geostatistical approach.
Siavash Salarian +3 more
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Multivariate linear QSPR/QSAR models: Rigorous evaluation of variable selection for PLS
Computational and Structural Biotechnology Journal, 2013 Basic chemometric methods for making empirical regression models for QSPR/QSAR are briefly described from a user's point of view. Emphasis is given to PLS regression, simple variable selection and a careful and cautious evaluation of the performance of ...
Kurt Varmuza +2 more
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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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Cross-validation in nonparametric regression with outliers [PDF]
, 2005 A popular data-driven method for choosing the bandwidth in standard kernel regression is cross-validation. Even when there are outliers in the data, robust kernel regression can be used to estimate the unknown regression curve [Robust and Nonlinear Time ...
Leung, Denis Heng-Yan
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Attribute Selecting in Tree-Augmented Naive Bayes by Cross Validation Risk Minimization
Mathematics, 2021 As an important improvement to naive Bayes, Tree-Augmented Naive Bayes (TAN) exhibits excellent classification performance and efficiency since it allows that every attribute depends on at most one other attribute in addition to the class variable ...
Shenglei Chen +2 more
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Assessing behavioural changes in ALS: cross-validation of ALS-specific measures [PDF]
, 2017 Objective: The Beaumont Behavioural Inventory (BBI) is a behavioural proxy report for the assessment of behavioural changes in ALS. This tool has been validated against the FrSBe, a non-ALS specific behavioural assessment, and further comparison of the ...
BR Brooks +16 more
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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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