Sentence examples for measure of predictive from inspiring English sources

Cross-validation methods were developed in the late 1970's as a way to incorporate a measure of predictive accuracy (and correspondingly, a measure of prediction error) for an estimated model based on its performance predicting the outcome for independent test cases [ 12].

RMSE serves as a measure of predictive power based on difference between observed and predicted values.

Here we utilize the mean squared error (MSE) i.e., the average of the squared differences between the model predictions and the actual values, as measure of predictive accuracy.

Drawing on the transcripts of seventy-eight thousand University of California freshmen from 1996 through 1999, the report found that, over all, the most useful statistic in predicting freshman grades was the S.A.T. II, which explained sixteen per cent of the "variance" (which is another measure of predictive validity).

The posture state (standing, sitting, lateral and sternal lying) was automatically classified for the full dataset with a mean F1 score (a measure of predictive performance between 0 and 1) of 0.78.

The evaluation was focused on two measures: the prediction error expressed by an integrated Brier score (IBS), and the ranked measure of predictive ability calculated as a time-truncated concordance index (C index).

For all three measures of predictive accuracy, regression trees resulted in predicted probabilities of 30-day mortality with both the lowest in-sample and out-of-sample accuracy (Table 3).

With the increasing use of case-cohort designs to answer questions relating to risk prediction, the methods presented in this paper will enable suitable measures of predictive ability to be computed and compared with studies of other designs.

Event rate (ER) and standard measures of predictive accuracy were calculated for both FRATs.

Furthermore, the presence of multiple subsets of predictors and associated models—helps find a better trade-off between different measures of predictive accuracy commonly adopted for hydrological modelling problems.

The ability of each type of fingerprint to predict similarity between molecules was determined using logistic regression, receiver operating characteristic (ROC) curves, and a range of measures of predictive success taken from the information retrieval and machine learning literatures.