Sentence examples for mean substitution weights from inspiring English sources

For every machine learning algorithm, the design that incorporated substitutions only when the mean substitution weights were at least 1 standard deviation above zero, outperformed the design that incorporated substitutions when the mean substitution weights were simply greater than zero.

Values for the mean and standard deviations for substitution weights calculated by each method are shown in Table 2.

These differences in turn arose from differences in calculated mean and standard deviations for the substitution weights (shown in Table 2), which themselves resulted from differences in the way in which the algorithms model the data.

Taking the mean substitution effectiveness of 0.5, substitution is preferable to sequestration.

One assumption for mean substitution is that missing values are missing completely at random (MCAR) [65].

Missing values were handled by mean substitution.

For missing values mean substitution was used.

The mean substitution rate was determined to be 4.64 × 10−4 substitutions per site, per year.

Uniform prior distributions were used for the mean substitution rates.

Missing data of independent variables were treated by mean substitution.

Mean substitution was used for replacing missing data.