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  2. EM algorithm and GMM model - Wikipedia

    en.wikipedia.org/wiki/EM_Algorithm_And_GMM_Model

    The EM algorithm consists of two steps: the E-step and the M-step. Firstly, the model parameters and the () can be randomly initialized. In the E-step, the algorithm tries to guess the value of () based on the parameters, while in the M-step, the algorithm updates the value of the model parameters based on the guess of () of the E-step.

  3. Expectation–maximization algorithm - Wikipedia

    en.wikipedia.org/wiki/Expectationmaximization...

    Itself can be extended into the Expectation conditional maximization either (ECME) algorithm. [35] This idea is further extended in generalized expectation maximization (GEM) algorithm, in which is sought only an increase in the objective function F for both the E step and M step as described in the As a maximizationmaximization procedure ...

  4. Determining the number of clusters in a data set - Wikipedia

    en.wikipedia.org/wiki/Determining_the_number_of...

    The average silhouette of the data is another useful criterion for assessing the natural number of clusters. The silhouette of a data instance is a measure of how closely it is matched to data within its cluster and how loosely it is matched to data of the neighboring cluster, i.e., the cluster whose average distance from the datum is lowest. [8]

  5. Generalized method of moments - Wikipedia

    en.wikipedia.org/wiki/Generalized_method_of_moments

    In econometrics and statistics, the generalized method of moments (GMM) is a generic method for estimating parameters in statistical models.Usually it is applied in the context of semiparametric models, where the parameter of interest is finite-dimensional, whereas the full shape of the data's distribution function may not be known, and therefore maximum likelihood estimation is not applicable.

  6. Multiple EM for Motif Elicitation - Wikipedia

    en.wikipedia.org/wiki/Multiple_EM_for_Motif...

    Multiple Expectation maximizations for Motif Elicitation (MEME) is a tool for discovering motifs in a group of related DNA or protein sequences. [ 1 ] A motif is a sequence pattern that occurs repeatedly in a group of related protein or DNA sequences and is often associated with some biological function.

  7. Minnesota Parents Who Locked Their Kids in Cages for ‘Their ...

    www.aol.com/minnesota-parents-locked-kids-cages...

    A Minnesota couple has reportedly been sentenced to four years after they locked their children in cages for "their safety." Benjamin and Christina Cotton from Red Wing, were sentenced by a ...

  8. Model-based clustering - Wikipedia

    en.wikipedia.org/wiki/Model-based_clustering

    Several of these models correspond to well-known heuristic clustering methods. For example, k-means clustering is equivalent to estimation of the EII clustering model using the classification EM algorithm. [8] The Bayesian information criterion (BIC) can be used to choose the best clustering model as well as the number of clusters. It can also ...

  9. 49ers suspend De'Vondre Campbell for refusing to enter game ...

    www.aol.com/report-49ers-suspend-devondre...

    The San Francisco 49ers on Monday suspended linebacker De'Vondre Campbell for the final three games of the regular season for refusing to play Thursday night against the Los Angeles Rams.. Niners ...