Sentence examples for linear regression scheme from inspiring English sources

StackingC employs a linear regression scheme to merge the predictions: the final predicted probability of a label is the linear combination of the probabilities predicted by participating algorithms; in other words, it is a weighted average of predictions where the weights for participating algorithms were learned from the training set through a nested cross-validation process.

The calibration curves were obtained by least square linear regression analysis using weight scheme as 1/ c (c=concentration) with Borwin software version 1.3.

For the two-tailed sampling scheme, linear regression showed the expected bias in parameter estimates but QTDTM with the correct α's, QTDTM with parental genotypes and the retrospective methods (with the different sets of α′ parameters) produced unbiased parameter estimates.

We show that under an SRS scheme, the linear regression estimator is a result of tuning the jackknife sample mean estimator with the chi-squared type distance function.

Under population stratification, Table 6 (online) shows that for all sampling schemes the simple linear regression method has increased type I error rates.

A Monte Carlo simulation is used to obtain the statistical properties of the Weibull parameters estimated by the linear regression, weighted linear regression and maximum likelihood schemes, respectively.

For testing the influence of hospital beds on scheme payments we used the linear regression model below.

For instance, the company was using a traditional linear regression algorithm for its credit scoring system.

Recently, Lee and Chang proposed an approach based on multiple linear regression technique [9] which employed a real-time noise classification scheme based on GMM.

Compared with previous shimming schemes, an improved matrix method combining multiple linear regression with systematic artificial adjustment is proposed.

In this paper we use a new scheme for efficient evaluation of the matrix entries for the linear regression method at an arbitrary point in the search space.