This function is a wrapper for a variety of plots, namely:
model performance across
alpha (to assess the relative performance among
different member models in the elastic net family, as well as in relation to permutation null models);
alpha, quality function across
lambda (to examine the selection of the optimal penalty parameter);
alpha, response vs out-of-bag predictions across instances (to assess
individual instances, examine outliers, etc);
(for categorical models) given
alpha, response vs out-of-bag predictions across classes;
alpha, caterpillar plot of feature statistics compared to permutation
null models (with statistical significance annotations for individual features); and
heatmap of feature statistics across
alpha (including statistical significance
annotations for individual features).
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Type of plot to be produced. Available plots
Integer indices to select
Additional plotting parameters.
Julian Candia and John S. Tsang
Maintainer: Julian Candia [email protected]
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## Not run: data(QuickStartEx) fit = eNetXplorer(x=QuickStartEx$predictor, y=QuickStartEx$response, family="gaussian", n_run=20, n_perm_null=10, seed=111) plot(x=fit,plot.type="summary") plot(x=fit,plot.type="lambdaVsQF",alpha.index=2) plot(x=fit,plot.type="measuredVsOOB",alpha.index=c(1,3,5)) plot(x=fit,plot.type="featureCaterpillar",stat="coef") plot(x=fit,plot.type="featureHeatmap",stat="freq") ## End(Not run)
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