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RobustEM (version 1.0)

Robust Mixture Modeling Fitted via Spatial-EM Algorithm for Model-Based Clustering and Outlier Detection

Description

The Spatial-EM is a new robust EM algorithm for the finite mixture learning procedures. The algorithm utilizes median- based location and rank-based scatter estimators to replace sample mean and sample covariance matrix in each M step, hence enhancing stability and robustness of the algorithm. To understand more about this algorithm, read the article ''Yu, K., Dang, X., Bart Jr, H. and Chen, Y. (2015). Robust Model- based Learning via Spatial-EM Algorithm. IEEE Transactions on Knowledge and Data Engineering, 27(6), 1670-1682. doi:10.1109/TKDE.2014.2373355''.

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Version

Install

install.packages('RobustEM')

Monthly Downloads

22

Version

1.0

License

GPL-3

Maintainer

Last Published

June 4th, 2015

Functions in RobustEM (1.0)

cluster_em_outlier

Clustering and Outlier Detection Algorithm
cluster_em

Clustering Algorithm
normalizedMI

Computes the normalized mutual information
matchCluster

Correspondence between clusters
trimmed_bic

Determines the number of components in the distribution.
cluster_plot

Clustering Plot
errorRate

This function calculates the error rates for the different EM algorithms
confusionMatrix

Confusion Matrix