DecisionTreeRegressor: DecisionTreeRegressor
In acca3003/ngboostR: R Wrapper for NGBoost python module
Description
Usage
Arguments
Value
Description
DecisionTreeRegressor
Usage
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DecisionTreeRegressor(
criterion = "friedman_mse",
min_samples_split = 2,
min_samples_leaf = 1,
min_weight_fraction_leaf = 0,
max_depth = 3,
splitter = "best",
random_state = NULL
)
Arguments
criterion
criterion
min_samples_split
min_samples_split
min_samples_leaf
min_samples_leaf
max_depth
max_depth
splitter
splitter
random_state
random_state
Value
DecisionTreeRegressor Object
acca3003/ngboostR documentation built on Dec. 18, 2021, 10:21 p.m.
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Description Usage Arguments Value
Description
DecisionTreeRegressor
Usage
1 2 3 4 5 6 7 8 9 | DecisionTreeRegressor(
criterion = "friedman_mse",
min_samples_split = 2,
min_samples_leaf = 1,
min_weight_fraction_leaf = 0,
max_depth = 3,
splitter = "best",
random_state = NULL
)
|
Arguments
criterion |
criterion |
min_samples_split |
min_samples_split |
min_samples_leaf |
min_samples_leaf |
max_depth |
max_depth |
splitter |
splitter |
random_state |
random_state |
Value
DecisionTreeRegressor Object
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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