Sentence examples for cross validating from inspiring English sources
The internal validity of the final model was checked by cross validating 500 bootstrap replicate to get bias corrected c-index with 95% CI [ 34, 37].
We applied a cross validation by first deriving the prediction model in the Erasmus MC-Sophia population and then cross validating the prediction model in the Haga-Juliana population and vice versa.
Briefly, cross validating a model is done by first splitting the data set into a number of equally sized partitions.
This sequence similarity-based clustering was useful in assigning the myosin classes to each of the hits and cross validating before we organized them into a database.
The proposed algorithm is capable of performing a dual task: cross validating disease target genes initially identified by gene expression and suggesting a pivotal role for new targets that could not be inferred from gene expression profiling alone.
The Mean Absolute Error (MAE) on test data unknown to the model with our best parameter combination was 0.09 (p < 0.0001, p was determined by re-training the model and cross validating datasets with shuffled affinity values).
The predictive ability of these signatures was evaluated by cross-validating the data as well as by validation in external and independent protein and mRNA data sets associated with clinical data.
The best assignment found by such calibration procedure by 10-folds-cross-validating the training set was (C, g) = (8,16).
This validation result mimics the approach an experienced investigator would take when identifying unknown compounds, by developing and tuning and cross-validating the algorithm on the training set and then applying the optimized parameters on the validation set.
The aim of this study was to assess the accuracy of an iPecs™ load cell during in situ human subject testing by cross-validating its force and moment measurements with those of a typical gait analysis laboratory.
Thanks to such a large data set, the selection of such relevant SAs can be carried out looking at the predictions obtained by cross-validating the SVM classifier on the training set; they are representative of its general prediction ability, so a filter fixing inaccuracies of such predictions will probably provide even for defects of the real model.
