# clusterEntropy: Calculation of per-cluster entropy

### Description

Provides the calculation of per-cluster entropy, equivalent to

Entropy(k) = ∑_{i \in C_k} \log (τ_{ik})

where τ_{ik} is the conditional probability of gene i belonging to cluster k and C_k corresponds to the set of indices of genes attributed to cluster k.

### Usage

 1 clusterEntropy(probaPost) 

### Arguments

 probaPost Matrix containing the conditional probabilities of belonging to each cluster for all observations

### Value

Entropy per cluster

### Author(s)

Cathy Maugis-Rabusseau

### Examples

 1 2 3 4 ## Generate artificial matrix of conditional probabilities for K=5 clusters tmp <- matrix(runif(100*5), nrow=100, ncol=5) probaPost <- tmp / rowSums(tmp) clusterEntropy(probaPost) 

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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