DashAI.back.models.HistGradientBoostingClassifier
- class HistGradientBoostingClassifier(**kwargs)[source]
Scikit-learn’s HistGradientBoostingRegressor wrapper for DashAI.
Methods
__init__
(**kwargs)decision_function
(X)Compute the decision function of
X
.fit
(x_train, y_train)Fit the estimator.
get_metadata_routing
()Get metadata routing of this object.
get_params
([deep])Get parameters for this estimator.
get_schema
()Generates the component related Json Schema.
load
(filename)Load the model of the specified path.
predict
(x_pred)Make a prediction with the model.
predict_proba
(X)Predict class probabilities for X.
save
(filename)Save the model in the specified path.
score
(X, y[, sample_weight])Return the mean accuracy on the given test data and labels.
set_fit_request
(*[, x_train, y_train])Request metadata passed to the
fit
method.set_params
(**params)Set the parameters of this estimator.
set_predict_request
(*[, x_pred])Request metadata passed to the
predict
method.set_score_request
(*[, sample_weight])Request metadata passed to the
score
method.staged_decision_function
(X)Compute decision function of
X
for each iteration.staged_predict
(X)Predict classes at each iteration.
staged_predict_proba
(X)Predict class probabilities at each iteration.
validate_and_transform
(raw_data)It takes the data given by the user to initialize the model and returns it with all the objects that the model needs to work.
Attributes
COMPATIBLE_COMPONENTS
TYPE
n_iter_
Number of iterations of the boosting process.