Sentence examples for example for regression from inspiring English sources

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It has been shown that such networks are able to approximate any continuous function with the required accuracy and therefore have a wide use, for example, for regression analysis [59].

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This property is shared by a large number of popular linear algorithms, collectively referred to as kernel methods, including for example, algorithms for regression, clustering or outlier detection (Schölkopf and Smola, 2002; Shawe-Taylor and Cristianini, 2004).

For example, for the regression method, it is possible to estimate uncertainty only due to the uncertainty in estimates of the mean regression fit.

Each plasmid and chromosome with more than 200 kb was considered as a learning example for the regression task of predicting the AAC of prokaryotic proteomes.

It was also unclear whether there was any relationship between the KS p-values and the "quality" of the MI inferences of primary interest (in our example for the regression coefficients).

For example, multiple linear regression, Poisson regression, and negative binomial regression models have been used to identify the relationship among accidents and contributing factors (e.g. data on mobility or on involved users).

If not published it is recommended to state the (i) endpoint, (ii) chemical class and (iii) statistical technique (for example: Linear regression model for the toxicity of anilines (pLC50) to algae (Pseudokircheriella subcapitata)).

For example, regression results for the same E18 experiment indicated LG burst onsets co-varied closely with TA cycle duration (Figure 3C1).

For example, published regression relationships for albacore tuna (Thunnus alalunga) show that for the average market size (12 kg), concentrations in tuna from the Mediterranean Sea (0.87 mg/kg) are higher than those in the Atlantic (0.47 mg/kg) and Pacific (0.17 mg/kg) oceans (Table 2).

For example, the regression coefficient for mother's high school completion was −0.15 for the complete case analysis, while it was approximately −0.2 for the four imputation models, suggesting that the data were not MCAR.

For example, the regression coefficients for each predictor in the model are often rounded to integers, which are then summed to produce a score.

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