Sentence examples for maximum likelihood parameters from inspiring English sources

Is there a meaningful qualitative description of how the discriminatively trained parameters differ from the maximum likelihood parameters?

Find the initial values of the maximum likelihood parameters which are mean, covariance, and mixing weights.

The data is then clustered around the maximum likelihood parameters as determined from the EM algorithm by the final estimates of the a posteriori probabilities at convergence.

Maximum Likelihood parameters (with relative errors) of the Double Branching model (seeEq. (1)) for the events of the JMA catalog above 100 km of depth (Mc = 5.0; Jan 1 1965 Dec 31 2008 , 5648events).

Table 2. Maximum Likelihood parameters (with relative errors) of the Double Branching model (see Eq. (1)) for the events of the JMA catalog above 30 km of depth (Mc = 5.0; Jan 1 1965-Dec 31 2008 , 1935events).

Basically, maximum likelihood algorithm is a statistical estimation algorithm used for finding log likelihood estimates of parameters in probabilistic models [30]. 1. Find the initial values of the maximum likelihood parameters which are mean, covariance, and mixing weights.

Correction for Bias in Maximum Likelihood Parameter Estimates Due to Nuisance Parameters.

When data points are known to have Gaussian probability distributions, maximum likelihood parameter estimation leads directly to least- squares estimation.

The distribution parameters are estimated using the maximum likelihood parameter estimation method.

A commonly used HMM-based synthesis is also performed with a Maximum Likelihood Parameter Generation algorithm for smoothing.

Maximum likelihood parameter estimates are obtained based on SEER data on the tumour size and stage of invasive breast cancer from patients who were symptomatically detected in the absence of screening mammography.