Sentence examples for Predictive modeling frameworks from inspiring English sources

Also, since the binary disease outcomes, typically in the form of case or control dichotomy, may not provide the most reliable study phenotypes, the predictive modeling frameworks might become more successful for predicting quantitative phenotypic traits [ 90- 92].

Related to this, while there are comparisons among various feature selection methods and predictive modeling frameworks on individual cohorts [ 23, 24, 27], there is not yet any definitive results whether one method will universally lead to optimal results in other subject cohorts or populations.

Among them are Weka (Waikato Environment for Knowledge Analysis) [1], RapidMiner [2], Keel (Knowledge Extraction based on Evolutionary Learning) [3], Orange [4], Scikit-learn [5], C1C2 [6] and KNIME (Konstanz Information Miner) [7], effectively, providing full predictive modelling frameworks.

There is an emerging body of research on deploying a systems perspective of the many factors affecting infectious disease risks, and there are now even early stage predictive modelling frameworks that show promise.

We present a scenario analysis to understand such consequences by integrating multi-disciplinary knowledge within a predictive modelling framework.

Here we combine an estimated dose response relationship from the data of Reddy et al. (2001) with data on the level of PCBs in the blubber of the Sarasota bottlenose dolphins (Wells et al. 2005) and the vital rates for this population (age-specific fecundity and survival from mark-recapture studies, Wells and Scott 1990) to develop a predictive model framework.

Predictive models, or action frameworks, are needed to organise existing knowledge and enable a more systematic approach to the selection and testing of intervention strategies.

One technique is called "predictive modeling".

Open image in new window Fig. 1 Three-step framework for predictive modeling.

The adoption framework (shown in Fig.  1) relies on predictive modeling, which can aid policy decisions by projecting possible outcomes.

To show the applicability of the identified model, the model is embedded within a nonlinear model predictive control (NMPC) framework to predict estimates of the control actions that comply with the process control objectives.