View the feature importance plot — gNetwork

gNetwork_view() Generate a feature importance plot for the random forest result. This plot visually highlights the importance of individual cluster within a dataset, helping to identify key factors in predictive modeling.

Usage

gNetwork_view(data)

Arguments

data: A dataframe; The output of gNetwork(), including 4 variables: weight, IncNodePurity, var_names and from. The weight is the edge value, the IncNodePurity(%IncMSE) is the measure of predictions as a result of var_names being permuted. from is the dependent variable in each round of random forest.

Examples

data(test_data)
gNetwork_view(test_network)
#> Warning: Removed 1 rows containing missing values (`geom_segment()`).
#> Warning: Removed 1 rows containing missing values (`geom_point()`).