Sentence examples for measure between models from inspiring English sources

As expected, the is the most discriminative performance measure between models.

Each one of these significant classifiers present in the minimum cover set and which are associated with one or more model (s) are compared with all such significant classifiers which are associated with other such model (s) and a similarity measure between these models has been computed from the classifiers present in these models using a correlation ratio measure as described in [147].

The ability of ISO 11948-1 (the Rothwell method) to predict the leakage performance of disposable bodyworn pads for heavy urinary incontinence was investigated by measuring correlations between models based on clinical evaluations of 138 diapers and inserts (the two major design categories), and technical models based on their Rothwell absorption capacities and design features.

Five metrics to measure framework invasiveness were proposed and applied to measure dependencies between model and framework code of several implementations of Thornthwaite and the Precipitation-Runoff Modeling System (PRMS), two well-known hydrological models.

The weighted sums of dissimilarity measurements from these two domains are used to measure the differences between models.

As an approximation, we have e − 1 2 Δ B I C = e − 1 2 (B I C M k − B I C M k ~ ) ≈ B F which is a measure that decides between models and accounts for high degrees of observational variation.

The method is also able to diagnosis multiple simultaneous disturbances by quantitatively measuring the similarities between models for different fault types.

Using the notion behind the DBC, we combine the robust discrepancy measure between a nested model M α and the full model with the measure of complexity of the model M α to define a robust model selection criterion in GLM.

The distance measure between Gaussian mixtures models is studied in Section 3. We describe our approach in Section 4. Section 5 presents simulation results under and without influence of noise.

Such an auxiliary input is designed to enlarge the distance measured by the Kullback discrimination information measure between the system models corresponding to the normal and the fault modes.

The models are clustered using pair-wise similarity or distance measures between a model pair as described earlier.