Sentence examples for implementing predictive models from inspiring English sources

All in all, the software presented here has the potential of becoming a widely used platform for implementing predictive models in production environments and promoting the collaboration between industry and academia.

Because predictive models always perform better on data on which they were generated than on new data, external validation is essential before implementing predictive models in clinical practice (16 18).

He is currently working to formalize the hypothesis mathematically and to implement predictive models of equity risk premium and other stock-­market returns using high-performance parallel processors.

In a similar way, we implemented predictive models for BMI at t3 and therapeutic alliance at t3 as the dependent variables.

This module aims to equip you with an understanding of what is involved in creating a predictive model before implementing predictive analytics techniques across digital marketing channels.

Our cerebellar model implemented predictive mechanisms related to the sensorimotor (short-timescale) predictions of the internal state of the arm, addressing thus, mainly the lower level.

Amongst many machine learning methods, neural network has been widely implemented for predictive modeling and shows excellent prediction performance compared to logistic regression [ 28- 31].

Amarasingham recently implemented a predictive model for diabetes patients who are at risk of complications within 90 days after leaving the hospital.

The machine learning (ML) method [ 20] implemented for predictive modeling in this pediatric traumatic brain injury study was originally designed for the prediction of acute cardiac complications, with an ensemble learning-based risk assessment as the core of decision making.

Case-based reasoning constitutes a viable alternative to the widely applied rule-based approach to reusing medical records for patient recruitment and can be successfully implemented using predictive modeling algorithms.

In fact, in previous studies on CM-MO samples [24, 67] depression scores – measured with the updated BDI-II [68] and not with the original BDI – were not correlated with frequency of headaches and, when implemented in a predictive model together with headache frequency and pain intensity, BDI-II scores had higher value in predicting disability and quality of life scores.