Sentence examples for by setting coefficients from inspiring English sources

LASSO is a coefficient shrinkage and variable selection method that achieves model sparsity by setting coefficients of many irrelevant transcripts to 0. The LASSO analysis was performed using the least angle regression (LARS) algorithm, utilizing 5-fold cross-validation, as implemented in the R package lars.

In prognostic studies, the lasso is particularly appealing for its ability to shrink regression coefficients and automatically perform variable selection by setting some coefficients to zero.

Different models are defined by setting some coefficients (ai) to 0. Hence, the probability of being infected only depends on the risk factors which associated coefficients are non-zero.

A trade-off is made between the two contradictory objectives by setting weight coefficients.

Finally, Wilms and Croux (2016) propose a sparse cointegration method for a large set of variables by setting some coefficients in the cointegration relationship at exactly zero.

For the assumed superposition modulation (7), this can be easily achieved by setting the coefficients as (L_{A,n}^{s}=2^{n}) and (L_{B,n}^{s}=operatorname {j}cdot 2^{n}).

Equal rate for all lengths is obtained by setting the coefficients of the linear terms and quadratic terms to zero in both equations.

In this analysis, differences in genotype frequency among populations were measured by GST [ 73, 74] Selection coefficients of the inoculated isolates within each host treatment were estimated simultaneously by setting the coefficient of the most-fit isolate (the isolate with the greatest increase in frequency over the considered time period) to zero as described previously [ 32].

By setting this coefficient to a high value (e.g. 100), air is effectively forced into flowing in the streamwise direction only.

For instance, a claim that one variable has no causal effect on another variable is a strong assumption encoded by setting the coefficient to zero.

A simpler model is obtained by setting the coefficient of log(Days) equal to 1 and fitting a linear model to log(Orangs1/Days1), the logarithm of the daily abundance.