Sentence examples for composition of training from inspiring English sources
The analysis of dynamics of those variations let us recommend an optimal composition of training data.
We used various performance criteria to evaluate the effectiveness of our system with the composition of training dataset.
Table 3 Composition of training and test sets used in the experiments Protein target ligands MDDR activity index Number of actives/number of inactives Train set Test set COX-2 inhibitors 78454 242/316 884/950 M1 agonists 09249 281/315 874/950 HIV PR inhibitors 71523 203/350 932/1100 Metalloproteinase inhibitors 78432 144/280 644/800 5-HT1agoniststs 06235 198/3406235/106235
This can guide the composition of training schedules.
We have also estimated the uncertainties arising from changing the composition of training dataset when some ncRNA families are removed.
Because of the stochastic nature of the algorithm, the composition of training and test sets is different for different original data set divisions.
The extent of this specific adaptation is influenced by multiple factors, such as genetic predisposition, hormonal influences, the neural component, muscle fiber composition, characteristics of training (frequency, intensity and duration), and others [ 1, 3].
Since the efficiency of the SWLR algorithm is sensitive to the class composition of the training data [ 44] we ensured that each training set consisted of roughly 50% responders and 50% non-responders.
Seventeen scenarios were investigated that can be divided into four groups according to composition of the training and validation data sets as follows: Scenarios 1 3: Training and validation data were subsets from the same population, DL, LW, and F1, respectively, i.e., prediction was within-population.
The answer probably depends on several factors, including selection intensity, effective size of the population, density of the SNP chip used, initial size of the training data, and whether or not the size and composition of the training data change over time.
However, since the composition of the training set remains the same in this method, it is not certain that the resultant model is optimal as there may be a bias in descriptor selection.
