Search results for "CROSS-VALIDATION"
showing 10 items of 50 documents
Cross-validation of the SCL-27: a short psychometric screening instrument for chronic pain patients
2001
We constructed a short multidimensional screening instrument for chronic pain patients based on the items contained in the Symptom Check List-90-Revised (SCL-90-R). The proposed dimensional structure of the SCL-90-R was recently shown to be irreproducible in chronic pain patients. As a consequence, the use of the Global Severity Index (GSI) was recommended, although it did not capture all information contained in the many items of the SCL-90-R. Based on an exploratory factor analysis, a six-dimensional structure using 27 items from the SCL-90-R was explored utilizing the data of 2780 chronic pain patients. A short form was prospectively tested on 581 patients in the same setting. Criteria f…
Cross-Validation of the Revised Version of the Violence Risk Appraisal Guide (VRAG-R) in a Sample of Individuals Convicted of Sexual Offenses.
2019
The aim of the present study was to examine the psychometric properties of the German version of the revised Violence Risk Appraisal Guide (VRAG), the VRAG-R. Therefore, VRAG-R ratings were made retrospectively in an Austrian sample of 534 individuals convicted of a sexual offense who were followed up with an average of 7.62 years. The VRAG-R showed large effect sizes for the predictive accuracy of violent (AUC = .75) and general recidivism (AUC = .78) and significant but rather small effect sizes (AUC = .63 and .61, respectively) in predicting any sexual and sexual contact recidivism. Furthermore, for the prediction of violent recidivism but not for sexual recidivism the VRAG-R was increm…
Mixed predictability and cross-validation to assess non-linear Granger causality in short cardiovascular variability series
2006
A method to evaluate the direction and strength of causal interactions in bivariate cardiovascular and cardiorespiratory series is presented. The method is based on quantifying self and mixed predictability of the two series using nearest-neighbour local linear approximation. It returns two causal coupling indexes measuring the relative improvement in predictability along direct and reverse directions, and a directionality index indicating the preferential direction of interaction. The method was implemented through a cross-validation approach that allowed quantification of directionality without constraining the embedding of the series, and fully exploited the available data to maximise th…
Spatiotemporal modeling and prediction of solar radiation
2003
[1] The radiation budget in the Earth-atmosphere system is what drives Earth's climate, and thus measurements of this balance are needed to improve our knowledge of Earth's climate and climate change. In the present paper we focus on the analysis of the surface shortwave radiation budget (SSRB), which is the amount of energy in the solar region of the electromagnetic spectrum (0.2–4.0 μm) absorbed at the surface. The SSRB has to be modeled from the surface to the top of the atmosphere, jointly with information about the state of the atmosphere and the surface. These data come from satellites orbiting the Earth and are often missing or disturbed. Its interest is not only at global scales; ra…
Hybrid kernel estimates of space-time earthquake occurrence rates using the Etas model
2010
The following steps are suggested for smoothing the occurrence patterns in a clustered space–time process, in particular the data from an earthquake catalogue. First, the original data is fitted by a temporal version of the ETAS model, and the occurrence times are transformed by using the cumulative form of the fitted ETAS model. Then the transformed data (transformed times and original locations) is smoothed by a space–time kernel with bandwidth obtained by optimizing a naive likelihood cross-validation. Finally, the estimated intensity for the original data is obtained by back-transforming the estimated intensity for the transformed data. This technique is used to estimate the intensity f…
Bivariate nonlinear prediction to quantify the strength of complex dynamical interactions in short-term cardiovascular variability.
2005
A nonlinear prediction method for investigating the dynamic interdependence between short length time series is presented. The method is a generalization to bivariate prediction of the univariate approach based on nearest neighbor local linear approximation. Given the input and output series x and y, the relationship between a pattern of samples of x and a synchronous sample of y was approximated with a linear polynomial whose coefficients were estimated from an equation system including the nearest neighbor patterns in x and the corresponding samples in y. To avoid overfitting and waste of data, the training and testing stages of the prediction were designed through a specific out-of-sampl…
Modified locally weighted—Partial least squares regression improving clinical predictions from infrared spectra of human serum samples
2012
Locally weighted partial least squares regression (LW-PLSR) has been applied to the determination of four clinical parameters in human serum samples (total protein, triglyceride, glucose and urea contents) by Fourier transform infrared (FTIR) spectroscopy. Classical LW-PLSR models were constructed using different spectral regions. For the selection of parameters by LW-PLSR modeling, a multi-parametric study was carried out employing the minimum root-mean square error of cross validation (RMSCV) as objective function. In order to overcome the effect of strong matrix interferences on the predictive accuracy of LW-PLSR models, this work focuses on sample selection. Accordingly, a novel strateg…
In silico prediction of central nervous system activity of compounds. Identification of potential pharmacophores by the TOPS–MODE approach
2004
The central nervous system (CNS) activity has been investigated by using a topological substructural molecular approach (TOPS-MODE). A discriminant analysis to classify CNS and non-CNS drugs was developed on a data set (302 compounds) of great structural variability where more than 81% (247/302) were well classified. Randic's orthogonalization procedures was carried out to allow the interpretation of the model and to avoid the collinearity among descriptors. The discriminant model was assessed by a leave-n-out (when n varies from 2 to 20) cross-validation procedure (79.94% of correct classification), an external prediction set composed by 78 CNS/non-CNS drugs (80.77% of correct classificati…
A kernel support vector machine based technique for Crohnâs disease classification in human patients
2017
In this paper a new technique for classification of patients affected by Crohnâs disease (CD) is proposed. The proposed technique is based on a Kernel Support Vector Machine (KSVM) and it adopts a Stratified K-Fold Cross-Validation strategy to enhance the KSVM classifier reliability. Traditional manual classification methods require radiological expertise and they usually are very time-consuming. Accordingly to three expert radiologists, a dataset composed of 300 patients has been selected for KSVM training and validation. Each patient was codified by 22 extracted qualitative features and classified as Positive or Negative as the related histological specimen result showed the CD. The eff…
A Large-Scale Empirical Evaluation of Cross-Validation and External Test Set Validation in (Q)SAR.
2013
(Q)SAR model validation is essential to ensure the quality of inferred models and to indicate future model predictivity on unseen compounds. Proper validation is also one of the requirements of regulatory authorities in order to accept the (Q)SAR model, and to approve its use in real world scenarios as alternative testing method. However, at the same time, the question of how to validate a (Q)SAR model, in particular whether to employ variants of cross-validation or external test set validation, is still under discussion. In this paper, we empirically compare a k-fold cross-validation with external test set validation. To this end we introduce a workflow allowing to realistically simulate t…