Random Forest Trees
Calculate Random Forest Trees instantly with the exact formula and a worked example.
Random Forest Trees
Library (1 = scikit-learn, 2 = R randomForest, 3 = R ranger)
Number of features p
Task (1 = classification, 2 = regression)
Default number of trees
100
Features per split (mtry / max_features)
10
Share of features per split
10%
More about: Random Forest Trees
What it calculates
The “Random Forest Trees” calculator computes Default number of trees from 3 parameters: library (1 = scikit-learn, 2 = r randomforest, 3 = r ranger), number of features p, task (1 = classification, 2 = regression).
Standard IT calculations for developers and sysadmins.
Example calculation
With parameters Library (1 = scikit-learn, 2 = R randomForest, 3 = R ranger) = 1, Number of features p = 100, Task (1 = classification, 2 = regression) = 1 the result is 100 (scikit-learn ≥ 1.1: n_estimators = 100; max_features = sqrt (classifier) or 1.0 (regressor)).
How to use
- Enter library (1 = scikit-learn, 2 = r randomforest, 3 = r ranger), number of features p and task (1 = classification, 2 = regression) — each field above is adjustable with a slider.
- Default number of trees is calculated automatically as you type.
- Check the worked example below to see the formula applied to real numbers.
- Copy the result or bookmark this calculator.
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FAQ
How is Random Forest Trees calculated?
The Random Forest Trees calculator computes Default number of trees from library (1 = scikit-learn, 2 = r randomforest, 3 = r ranger), number of features p, task (1 = classification, 2 = regression). Enter your values above and the exact formula is applied instantly; a worked example with real numbers is shown below.
Is the Random Forest Trees calculator free?
Yes. It is completely free, needs no signup, runs entirely in your browser, and sends no data to any server.
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