Sentence examples for maximizing the predictive from inspiring English sources

In this paper, we propose a statistical data-driven method to address this challenge by minimizing the number of biomarkers in the screening procedure while maximizing the predictive power over a broad spectrum of diseases.

The optimal parameter values are chosen by using the RF estimate in the LN model to simulate responses to the training stimulus (with f also estimated from the training data as in [20]) and maximizing the predictive power measured as the correlation coefficient between the simulated and actual responses.

In contrast to the conventional population-level association testing, which often detect only a few variants with statistical support beyond the genome-wide significance level (e.g. p < 10-8), machine learning algorithms place special emphasis on maximizing the predictive accuracy at the level of individual subjects.

Specifically, we use the penalty strength that maximizes the predictive correlation in within-cohort prediction in Croatia.

Here's what organizations need to know in order to minimize potential risks and maximize the predictive accuracy of these tests.

Instead of finding the best ones for each disease separately, decide first how many biomarkers you want — the researchers settled on 30 — and then maximize the predictive power, over all possible combinations, for the whole set of diseases at once.

The search process is based on a four-objective optimization problem that minimizes the number of selected predictors, maximizes the predictive accuracy of a data-driven model and optimizes two information theoretic metrics of relevance and redundancy, which guarantee that the selected subsets are highly informative and with little intra-subset similarity.

Modeling techniques are then aggregated to maximize the predictive power of the wellness score.

This is why we wanted to optimize and maximize the predictive value of the initial evaluation to establish a thinner selection of cirrhotic candidates for admission in ICU.

The reason is that the selection aims to maximize the predictive power of the covariates, which is captured by the reduced forms rather than by the equation of interest (9).

It is worth noting that the role of the propensity score model specification is not to maximize the predictive capability of the model but to balance the distribution of relevant pre-treatment covariates between treated and untreated individuals.