odte/docs/source/hyperparameters.md

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Hyperparameters

Hyperparameter Type/Values Default Meaning
estimator <sklearn.BaseEstimator> Stree() Base estimator used to build each element of the ensemble.
n_jobs <int> -1 Specifies the number of threads used to build the ensemble (-1 equals to all cores available)
random_state <int> None Controls the pseudo random number generation for shuffling the data for probability estimates. Ignored when probability is False.
Pass an int for reproducible output across multiple function calls
max_features <int>, <float>

or {“auto”, “sqrt”, “log2”}
None The number of features to consider in each tree:
<int> max_features features for each tree.
<float> max_features is a fraction and int(max_features * n_features) features are considered for each tree.
“auto” max_features=sqrt(n_features)
“sqrt” max_features=sqrt(n_features)
“log2” max_features=log2(n_features)
None max_features=n_features
max_samples <int>, <float> None The number of samples to consider for bootstrap:
<int> max_samples samples for each tree.
<float> max_samples is a fraction and int(max_samples * n_samples) samples for each tree.
n_estimators <int> 100 The number of trees the ensemble is going to build
be_hyperparams <str> "{}" Hyperparameteres passed to the base estimator, i.e. "{\"C\": 17, \"kernel\": \"rbf\"}"