Is it possible to calculate the Approximate Weight of Evidence (AWE) from information obtained via the mclust R package?
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Following the formula from Banfield, J. and Raftery, A. (1993) Model-based Gaussian and non-Gaussian clustering. Biometrics, 49, 803-821. -2*model$loglik + model$d*(log(model$n)+1.5) Where model represents the model with number of cluster solutions selected. Keeping this question in the hope that it may help someone in the future.
jmutr
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Is there a reason not to use the in-built function `awe()`, which is based on the same paper you cite here? – Daemon Painter Dec 08 '19 at 19:05
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According to R documentation, you should have access to function awe(tree, data) since version R1.1.7.
From the example on the linked page (in case of broken link),
data(iris)
iris.m _ iris[,1:4]
awe.val <- awe(mhtree(iris.m), iris.m)
plot(awe.val)
Daemon Painter
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I did try that formula beforehand and it did not recognize the formula. Thought that perhaps the formula was removed, but could be mistaken. Will check again later, thanks for the answer! – jmutr Dec 09 '19 at 20:03