plotClassifierROC: Diagnostic plots for pathClassifier.

Description Usage Arguments Value Author(s) See Also

Description

Diagnostic plots for pathClassifier.

Usage

1

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


aiminy/NetPathMiner documentation built on May 12, 2019, 3:38 a.m.