Sentence examples for numeric I from inspiring English sources

Exact(1)

This level was once called the University Division of the NCAA, and the Division II and III levels, the College Division; this terminology was replaced with the current numeric (I, II, III) divisions in 1973.

Similar(58)

Averaging is the most fundamental and common combination method for numeric output (i.e. regression problem), while voting is a common combination method for nominal output (i.e. classification problem).

In this study, numeric parameters (i.e., flow velocity, component size, component thickness, misalignment angle, as well as the length and width of the FPCB) were optimized using response surface methodology (RSM) with the central composite design technique.

Four factors five levels central composite rotatable design was used to develop relationship for predicting dilution, which enables to quantify the direct and interactive effects of four numeric factors i.e. wire feed rate, open circuit voltage, welding speed and nozzle-to-plate distance and one categorical factor preheat current.

The researchers grouped the students into 10 groups based upon their numeric grades (i.e., a 1 100 continuous scale) in the first year of medical school.

The additional benefit from the above rescaling is that instead of specifying of numeric values W i, B i req, M i, and k i ( p ) separately, we have to specify b i ( p ) only.

Part of why I'm being so optimistic for Bernie is for numeric reasons, I have to admit.

The numeric classification (I-VII) is somewhat confusing, as the characteristics of each type overlap.

The non-numeric variables (i.e. bottom cover, dominant substratum, aquatic and terrestrial vegetation) were excluded from analyses.

In the first step, we must specify how the numeric inputs u i ∈U i for the CPU utilisation rates are converted to fuzzy sets (a process that called "fuzzification" [18]) so that they can be used by the FLS.

To demonstrate the capability of the computational model, the GA SVR modeling results were compared with those obtained using numeric predictive models (i.e., classification and regression tree, chi-squared automatic interaction detector, multiple regression, artificial neural network, and ensemble models) and empirical methods.

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