Search results
Results from the WOW.Com Content Network
In structural engineering, the Structural Identification using Expectation Maximization (STRIDE) [26] algorithm is an output-only method for identifying natural vibration properties of a structural system using sensor data (see Operational Modal Analysis). EM is also used for data clustering.
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.
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]
One prominent method is known as Gaussian mixture models (using the expectation-maximization algorithm). Here, the data set is usually modeled with a fixed (to avoid overfitting) number of Gaussian distributions that are initialized randomly and
k-SVD is a generalization of the k-means clustering method, and it works by iteratively alternating between sparse coding the input data based on the current dictionary, and updating the atoms in the dictionary to better fit the data. It is structurally related to the expectation–maximization (EM) algorithm.
The slow "standard algorithm" for k-means clustering, and its associated expectation–maximization algorithm, is a special case of a Gaussian mixture model, specifically, the limiting case when fixing all covariances to be diagonal, equal and have infinitesimal small variance.
Also, the convergence of the algorithm in higher dimensions with a finite number of the stationary (or isolated) points has been proved. [5] [7] However, sufficient conditions for a general kernel function to have finite stationary (or isolated) points have not been provided. Gaussian Mean-Shift is an Expectation–maximization algorithm. [8]
Pages in category "Cluster analysis algorithms" ... Data stream clustering; DBSCAN; E. Expectation–maximization algorithm; F.