ImportancePlot: Plot the feature importance
In zh542370159/dropSplit: Automatically identify cell-containing and empty droplets for droplet-based scRNAseq data using dropSplit
ImportancePlot R Documentation
Plot the feature importance
Description
Plot the feature importance
Usage
ImportancePlot(meta_info, train, importance_matrix, top_n = 20)
Arguments
meta_info
importance_matrix generated by dropSplit.
train
train dataset generated by dropSplit.
importance_matrix
importance_matrix generated by dropSplit.
top_n
Number of the top important features to plot.
Value
A a list of ggplot objects.
Examples
counts <- simSimpleCounts()
result <- dropSplit(counts)
pl <- ImportancePlot(result$meta_info, result$train, result$importance_matrix, top_n = 20)
pl$Importance
pl$preDefinedClassExp
zh542370159/dropSplit documentation built on June 19, 2022, 2:49 p.m.
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| ImportancePlot | R Documentation |
Plot the feature importance
Description
Plot the feature importance
Usage
ImportancePlot(meta_info, train, importance_matrix, top_n = 20)
Arguments
meta_info |
|
train |
|
importance_matrix |
|
top_n |
Number of the top important features to plot. |
Value
A a list of ggplot objects.
Examples
counts <- simSimpleCounts() result <- dropSplit(counts) pl <- ImportancePlot(result$meta_info, result$train, result$importance_matrix, top_n = 20) pl$Importance pl$preDefinedClassExp
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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