A powerful finite mixture model based on the generalized Dirichlet distribution: unsupervised learning and applications This paper presents a new finite mixture model based on a generalization of the Dirichlet distribution. For the estimation of the parameters of this mixtur... N Bouguila,D Ziou -...
Define Expectation value. Expectation value synonyms, Expectation value pronunciation, Expectation value translation, English dictionary definition of Expectation value. n. 1. A quantity expressing a typical or average value of a random variable. 2. The
In this paper, we constructed an unsupervised learning algorithm and focused on a finite mixture model based on multivariate Beta distribution. Our motivation is the flexibility and high potential that this distribution offers in modeling data. To learn this mixture model, we used an expectation ...
Beta-Liouville distributionFacial expressionAction recognitionWe propose a nonparametric Bayesian model for the clustering of proportional data. Our model is based on an infinite mixture of Beta-Liouville distributions and allows a compact description of complex data. The choice of the Beta-Liouville as...
Expectation identityHigh-order momentsFor the variance parameter of the hierarchical normal and inverse gamma model, we analytically calculate the Bayes rule (estimator) with respect to a prior distribution IG(alpha,beta) under Stein's loss function. This estimator minimizes the posterior expected ...
The mathematical expectations of Bernoulli-distributed white sequences can be taken as [[alpha].sub.1] = 0.5, [[alpha].sub.2] = 0.4, [[beta].sub.1] = 0.3, [[beta].sub.2] = 0.2, [[gamma].sub.1] = 0.4, and [[gamma].sub.2] = 0.3. Design of Nonfragile State Estimator for...
Sampling-Reconstruction Procedure of Gaussian Processes With Jitter Characterized by the Beta Distribution The sampling-reconstruction procedure of different Gaussian processes with jitter and with a limited number of samples is investigated. We suggest a new mo... VA Kazakov,D Rodriguez S. - 《IEEE ...
To model the joint distribution over the multi-scale of protein and drug interactions, a few attempts have been developed14,15,16,17. An intuitive approach for learning multi-scale representations is to combine the molecular graph with an interaction network and optimize them jointly. For example...
Thus, we can think of g(y)=E[X|Y=y]g(y)=E[X|Y=y] as a function of the value of random variable YY. We then write g(Y)=E[X|Y].g(Y)=E[X|Y]. We use this notation to indicate that E[X|Y]E[X|Y] is a random variable whose value equals g(y)=E[X|Y=y]g(y...
Motif distribution analysisFor visualizing the distribution of motifs in the sequence set, you need to generate either a .occurrence file by executing BaMMmotif with a --scoreSeqset flag or by executing BaMMScan.Either${HOME}/opt/BaMM/bin/BaMMmotif [OUTPUT_FIR] [FASTAFILE] [MOTIF_FILE] [...