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BARTHyperparameters

Variant

Bayesian Additive Regression Trees (stochtree). See `setup_BART`.

Raw JSONv1Unknown properties rejected

Properties

num_trees
integer | object≥ 1

Number of trees in the mean forest.

alpha
number | object> 0< 1

Base of the tree split prior alpha * (1 + depth)^-beta.

beta
number | object≥ 0

Depth penalty exponent of the tree split prior alpha * (1 + depth)^-beta.

min_samples_leaf
integer | object≥ 1

Minimum number of training cases in a leaf. Cannot exceed the number of cases in the training data.

max_depth
integer | object | null≥ 1

Maximum depth of any tree. NULL imposes no limit.

num_features_subsample
integer | object | null≥ 1

Number of features subsampled when growing each tree. NULL uses every feature. Cannot exceed the number of features in the training data.

variance_forest_num_trees
integer | object≥ 0

Number of trees in the conditional variance forest. 0 fits a homoskedastic model.

num_gfr
integer≥ 0

Number of grow-from-root warm-start iterations.

num_burnin
integer≥ 0

Number of burn-in MCMC iterations.

num_mcmc
integer≥ 1

Number of retained MCMC iterations per chain.

num_chains
integer≥ 1

Number of independent MCMC chains. Cannot exceed num_gfr unless num_gfr is 0.

keep_every
integer≥ 1

Thinning interval: retain one MCMC sample in every keep_every.

cutpoint_grid_size
integer≥ 1

Maximum number of candidate cutpoints considered by the grow-from-root algorithm.

standardize
boolean

Center and scale the outcome before sampling.

link
string

Link function of the binary outcome model (classification only). "cloglog" cannot be combined with case weights.

one of"probit""cloglog"

seed
integer | null

Random seed for the sampler. NULL leaves the sampler seeded by the system.

ifw
boolean | object

Inverse Frequency Weighting in classification.

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