Exact(3)
View preference distributions are triangular and bimodal, with maximum probability p c equal to 50%%.
View preference distributions are Gaussian and bimodal, with maximum probability p c equal to 50%% (top) and 35%% (bottom).
We are explicitly setting the maximum probability p of the logistic function on a per-component basis, drawing from a global p ∼ Beta (α h p, β h p ). Then λ is set for each component as a global hyperparameter, λ.
Similar(5)
For each interaction e, we calculate the optimal alternative path P with maximum probability w(P) between the corresponding proteins in the current scaffold.
Using Bayes' rule, one can predict the sublineage for new data by determining the sublineage with maximum probability: (3) P (C ∣ S Ω, R Ψ ) ∝ ∏ j ∈ Ω (∑ H j ∈ { 0,1 } P (S j ∣ H j ) P (H j ∣ C ) ) × P (C ∣ R Ψ ) P (R Ψ ).
By statistical recognition is meant the feature vector y extracted from test HRRP sample x will be assigned to the class with maximum posterior probability p(c|y), where c ∈ {1,..., C} denotes the class membership.
For the case of the mouse retina data, we consider maximum link probability p m a x ∈ { 0.95, 0.9, 0.7 }, variance scales for the synapse density profile of σ 2 ∈ { 0.01, 0.1, 1.0 } (of normalized depth), and K ∈ { 2, 3 } possible synapse density profile mixture components.
Since dialysis patients are already in a less than ideal health state it is easier for them to specify the maximum probability 1-p of the unfavorable outcome rather than the minimum probability p of the favorable one.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com