Last data update: 2014.03.03
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Cran Task View
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SMO (statistical methods ontology)
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mRMRe.Network is a wrapper for inferring a network of features based on mRMR feature selection.
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The feature count is simply the total number of samples considered in the mRMRe procedure.
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The scores method returns the scores of individual features in respect to previously selected features as per standard mRMR procedure. For each target, the score of a feature is defined as the mutual information between the target and this feature minus the average mutual information of previously selected features and this feature.
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Correlate is a function that cestimates correlation between two variables, which can be either continuous, categorical (ordered factor) or censored (survival data).
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The causality data is compute using the co-information lattice algorithm on each V-structure (feature, target, feature). Given that this procedure is computed for each pair of features, the minimum result is kept. A negative score indicates putative causality of the feature to the target.
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mRMRe.Data is the class containing datasets. Most if not all of the routines in the mRMRe package use mRMRe.Data objects as primary input.
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mRMRe.Filter is a wrapper for various variants of the maximum relevance minimum redundancy (mRMR) feature selection/filter.
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The feature count is simply the total number of feature considered in the mRMRe procedure.
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The adjency matrix is a directed matrix of 0's and 1's indicating if there is a link between features.
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TODO
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providing 
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