The phrase "average number of models" is correct and usable in written English.
It can be used when discussing statistical data or analysis related to a specific quantity of models in a given context.
Example: "The average number of models produced by the factory each month has increased significantly over the past year."
Alternatives: "mean quantity of models" or "typical count of models".
While, in our data set, the average number of model variants offered annually by each manufacturer is 45 (disregarding 'all other makes'), MB have split their sales among, on average, 206 different model variants, with a mean sale of only 15 cars per model variant per year.
Table 2 Aggregate number of new automobiles sold, mean number of model variants offered per year, and average number of vehicles sold annually per model variant, by make.
Although such prediction is too inaccurate for most purposes, we demonstrate with a Naïve Bayes Classifier that it is accurate enough to more than double the average number of acceptable models retained during the crucial filtering stage of protein docking when combined with our constrained docking algorithm.
To identify the cars no one wants to buy, 24/7 Wall St. reviewed the highest average number of days car models spent on dealers' lots before they were sold in 2014 from Kelley Blue Book (KBB).
All those models are genome-scale, the average number of reactions per model is 2 879.
For example, the average number of annotations per model, as well as the minimum, maximum and the standard derivation, can be computed for the set of SBML and CellML models available from BioModels Database and the CellML Model Repository, respectively (Query 7).
Query 7: What is the minimum, maximum and average number of annotations per model?
MATCH (m:SBML_MODEL <-[:BELONGSBML_MODEL <-[ANNOTATION)<-[:BELONGS_TO*1..2]- a ANNOTATION <-[ Model, count(r) AS NumBELONGS_TO*1..2]- a ANNOTATION <-[fAnnotation), min(NumBELONGS_TO*1..2]- a ANNOTATION <-[tation), stdev(NumBELONGS_TO]- rn) Query 7: What is the minimum, maximum and average numBELONGS_TO]- rions peRESOURCE
Table 4 summarizes Spice's skill on two-class microarray data using five metrics: accuracy and its variance, sensitivity, specificity, precision, and F1-measure; it also reports an average number of features per model.
Average number of factors used in model construction.
