We designed the proposed predictor (which includes selection of features that are used to encode the inputs, parameterization of the Support Vector Machine (SVM -based claSVM -basednd seleclassifierse threshold for the predicted disorder probandlitieselectionin binary predictiofs) using 5-fold cross validathen on thresholdataset.
We designed the proposed predictor, which includes filtration of the considered features, parameterization of the SVM-based classifiers, feature selection and selection of the thresholds for the aggregation of the four predictors (which are described below), using 5-fold cross-validation on the training datasets.
A high-performance three-stage model was developed with AOD, meteorological, demographic and land use variables as predictors, which includes a custom-designed PM2.5 gap-filling method.
Of the risk scores, QRISK2 had the most predictors, which included disease conditions such as atrial fibrillation and chronic renal disease.
Multiple linear regression analyses were used to assess the association between HRQOL (proxy- and self-rated HRQOL scores) and related predictors, which included health status, severity of the main health problem, and status of medication use.
For instance, Krumholz et al. reviewed 2,176 patients in 18 hospitals and derived a model comprising four independent predictors, which included hospitalization in the prior year, medical history of HF, medical history of diabetes mellitus, and serum creatinine levels at discharge [ 9].
We used fire frequency as the response variable and a set of 28 potential predictor variables, which included climatic, human, topographic, biological and hydrological factors.
Merlo et al. (2014) observed that, in comparison to models without wood density as a predictor, models which included density had R 2 values that were about 4 9%% higher.
The 110 belt transects (55 from each season) were modeled simultaneously against 17 predictor variables, which included continuous environmental data, count data, and categorical terms (Table 1).
Multivariate analysis for each outcome variable was separately done after controlling for the rest of the predictor variables, which included age, gender, BMI, SES, parental understanding, parental check and close friends.
We compiled a list of potential predictor variables, which included established risk factors for each outcome from the literature or existing risk prediction scores, using similar definitions when possible.
