Comments (1)
Hi Robert,
This is the correct place for these types of questions and requests.
Regarding stratified sampling, the DT package does not provide such support. You could use the StratifiedRandomSub
function included in the MLBase.jl package, and feed the sampled records to the tree builder.
Trees and forests are immutable, so in order to modify them, you'd need to create new ones. To merge forests, you could just concatenate their trees, ex:
merged_forest = Ensemble([forest1.trees, forest2.trees])
You could merge individual trees into an ensemble in a similar fashion, and then use the apply_forest
function to make predictions.
from decisiontree.jl.
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from decisiontree.jl.