Sentence examples for maximum probability criterion from inspiring English sources

State membership of individual probes is determined by the maximum probability criterion.

Cluster memberships of samples were then obtained in a hard/soft fashion using a maximum probability criterion.

Since the maximum probability criterion assigns test samples to classes without regard to how large the maximal posterior class probabilites are, we tested the robustness of our results by only classifying samples passing a minimum probability threshold.

With hypomethylated genes only, the Venn diagram for the overlap of genes with expression alteration between the two drug-resistant cell lines is shown in Figure 5 (based on maximum probability criterion).

This model selection step is a cluster-inference procedure that yields estimates for(τ kj, μ kj,Σ kj, G k ), from which classification of test samples proceeds as before using the maximum probability criterion.

The probability that y belongs to class k is just the posterior probability p k| y), which by Bayes' Theorem can be written as (2) p (k | y ) = π ^ k f k (y | θ ^ k ) ∑ c = 1 C π ^ c f c (y | θ ^ c ) Assigning y to the class which maximises this posterior probability (the maximum probability criterion) minimises the expected misclassification error.

With the maximum membership probability criterion, the assignment by STRUCTURE showed for 94.4% of the inbreds correspondence with the germplasm type information.

Relying on maximum a posteriori probability criterion and particle filtering technology, a joint estimation algorithm of the time-variant channel gain and primary user state is presented.

Applying the maximum pair consistency probability criterion, the three continuous variables are categorized, assuming that qtc is a normal variable, t a log-normal variable and bt a variable with a common central tendency.

On parallel, the change detection methods have been developed based on the maximum a posteriori (MAP) probability criterion which use MRFs as a priori models [11 13].

They are based on Neymann-Person optimum criterion providing the maximum probability of detection for a given false alarm rate.