Description Usage Arguments Value Examples
Decision tree voting scheme. Implements a feature selection approach based on Decision Trees, using a voting scheme across the top levels on trees trained on multiple subsamples.
1 | dtreevoting(num_runs = 100, num_levels = 10, file_path = file_path)
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num_runs |
Number of subsamples to use for voting scheme (default: 100) |
num_levels |
Number of levels in each tree to consider. Only the features which appear in the top num_levels levels of the trees (from the root) will be counted |
file_path |
Where the num_runs subsample files are found (e.g. if sample 10 is at 'subsamples/sample10.csv' then file_path should be 'subsamples/sample'). There must be enough samples to fulfill num_runs runs. |
Outputs a dataframe containing (first column) total number of appearances of each feature (each row is a feature). The rest of the columns represent 1 run each and contain the level at which the feature appears.
1 2 3 4 | dtreevoting(
num_runs=5,
num_levels=10,
file_path=paste(system.file('samples/subsamples', package = "feamiR"),'/sample',sep=''))
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