plotClassifierROC {NetPathMiner} | R Documentation

## Diagnostic plots for pathClassifier.

### Description

Diagnostic plots for `pathClassifier`.

### Usage

    plotClassifierROC(mix)

### Arguments

`mix` | The result from `pathClassifier`.

### Value

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.

### Author(s)

Timothy Hancock and Ichigaku Takigawa

### See Also

Other Path clustering & classification methods: `pathClassifier`, `pathCluster`, `pathsToBinary`, `plotClusterMatrix`, `plotPathClassifier`, `plotPathCluster`, `predictPathClassifier`, `predictPathCluster`

Other Plotting methods: `colorVertexByAttr`, `layoutVertexByAttr`, `plotAllNetworks`, `plotClusterMatrix`, `plotCytoscapeGML`, `plotNetwork`, `plotPathClassifier`, `plotPaths`

[Package NetPathMiner version 1.16.0 Index]