Sentence examples for it is simple to compute from inspiring English sources

For classification problems, the Fisher Discriminant Ratio [64] is often used because it is simple to compute and reliable for binary classification problems.

The local monotone Lax-Friedrichs numerical flux is a particularly convenient choice of numerical flux because it can easily be applied to any nonlinear hyperbolic system, it is simple to compute, and it yields good results, although there are many other numerical fluxes which could also be used [24].

The advantage of the discrimination index is that it is simple to compute and explain [ 26].

In the case of RNA secondary structures, it is simple to compute the total number of secondary structures by dynamic programming, given as follows.

Although there is no direct biological evidence for DCJ operations, these operations are very attractive because it provides a unifying model for genome rearrangement [ 12] and it is simple to compute the DCJ distance.

We get Having shown how to compute the p-value of a given entropy or parsimony score under a fixed codon rate matrix, it is simple to compute posterior p-values for the case where the functional class is not known in advance.

Due to the independence of random variables in the transform domain, it is simpler to compute the statistics of interest, and afterwards the transform is inverted to get the desired result.

Compared with MLA and GEE, the MH procedure is simple to compute, it is fairly intuitive and it does not require any assumptions for binomial data.

On the basis of a simple Cox proportional hazards model and using routinely collected data on tumour stage, size, and grade, the NPI is simple to compute, its predictions demonstrate good discriminative ability, and it has been successfully validated (Todd et al, 1987; Galea et al, 1992; Sundquist et al, 1999).

Although the Euclidean distance measure is simple to compute and is limited to linear relationships between samples, it has been shown through different empirical experiments that the similarity measure using the Euclidean distance achieves comparable results to more advanced similarity measures (e.g., nonlinear similarity measures).

A 1D approximation is simple to compute, which leads to a rapidly converging model.