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huge.roc

Draw ROC Curve for a graph path


Description

Draws ROC curve for a graph path according to the true graph structure.

Usage

huge.roc(path, theta, verbose = TRUE)

Arguments

path

A graph path.

theta

The true graph structure.

verbose

If verbose = FALSE, tracing information printing is disabled. The default value is TRUE.

Details

To avoid the horizontal oscillation, false positive rates is automatically sorted in the ascent order and true positive rates also follow the same order.

Value

An object with S3 class "roc" is returned:

F1

The F1 scores along the graph path.

tp

The true positive rates along the graph path

fp

The false positive rates along the graph paths

AUC

Area under the ROC curve

Note

For a lasso regression, the number of nonzero coefficients is at most n-1. If d>>n, even when regularization parameter is very small, the estimated graph may still be sparse. In this case, the AUC may not be a good choice to evaluate the performance.

See Also

Examples

#generate data
L = huge.generator(d = 200, graph = "cluster", prob = 0.3)
out1 = huge(L$data)

#draw ROC curve
Z1 = huge.roc(out1$path,L$theta)

#Maximum F1 score
max(Z1$F1)

huge

High-Dimensional Undirected Graph Estimation

v1.3.4.1
GPL-2
Authors
Haoming Jiang, Xinyu Fei, Han Liu, Kathryn Roeder, John Lafferty, Larry Wasserman, Xingguo Li, and Tuo Zhao
Initial release

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