View source: R/pathClassifier.R
plotClassifierROC | R Documentation |
Diagnostic plots for pathClassifier
.
plotClassifierROC(mix)
mix |
The result from |
Diagnostic plots of the result from pathClassifier.
itemTopROC curves for the posterior probabilities (mix\$posterior.probs
)
and for each HME3M component (mix\$h
). This gives information about what response
label each relates to. A ROC curve with an AUC < 0.5
relates to y = 0
.
Conversely ROC curves with AUC > 0.5
relate to y = 1
.
itemBottomThe likelihood convergence history for the HME3M model. If the parameters
alpha
or lambda
are set too large then the likelihood may decrease.
Timothy Hancock and Ichigaku Takigawa
Other Path clustering & classification methods:
pathClassifier()
,
pathCluster()
,
pathsToBinary()
,
plotClusterMatrix()
,
plotPathClassifier()
,
plotPathCluster()
,
predictPathClassifier()
,
predictPathCluster()
Other Plotting methods:
colorVertexByAttr()
,
layoutVertexByAttr()
,
plotAllNetworks()
,
plotClusterMatrix()
,
plotCytoscapeGML()
,
plotNetwork()
,
plotPathClassifier()
,
plotPaths()
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