Sentence examples for modern modelling techniques from inspiring English sources

Based on a number of examples it demonstrates the use of modern modelling techniques in the design and analysis of sub-systems in measurement technology.

Modern modelling techniques may potentially provide more accurate predictions of binary outcomes than classical techniques.

Modern modelling techniques such as SVM, NN and RF may need over 10 times as many events per variable to achieve a stable AUC and a small optimism than classical modelling techniques such as LR.

We compared three relatively modern modelling techniques: support vector machines (SVM), neural nets (NN), and random forests (RF) and two classical techniques: logistic regression (LR) and classification and regression trees (CART).

Modern modelling techniques, such as SVM, NN and RF, needed far more events per variable to achieve a stable validated AUC and an optimism <0.01 than the more conventional modelling techniques, such as LR and CART.

Modern modelling techniques such as SVM, NN and RF need far more events per variable to achieve a stable AUC-value than classical modelling techniques such as LR and CART.

With the advent of modern supercomputing and advanced modeling techniques, studying and designing these engines through detailed simulations is becoming tractable.

The ability to extract crystallographic information from 3D atomistic reconstruction has exciting potential synergies with modern modeling techniques, blending experimental and computational methods to extend our insight.

However, the current study provides an example for how modern modeling techniques can adjust for observed differences between cohorts.

This study highlights both the challenge of collecting suitably informative field data with which to characterise subsurface hydrology, and the power of modern calibration and uncertainty modelling techniques to assess flow path uncertainty in hillslopes and other small scale systems.

Little is known, however, about the sample size that is needed to generate a prediction model with a modern modelling technique that outperforms more traditional, regression-based modelling techniques in medical data.