Call shutil.copy() with logging

Dispatch for meta info.

Get split value histogram of a feature Parameters ---------- feature : The name of the feature. fmap:

Synthesize a test dataset with changed encoding.

Number of features in booster.

Get the number of non-missing values in the DMatrix. .. versionadded:: 1.7.0

Predict with `X`. If the model is trained with early stopping, then :py:attr:`best_iteration` is used automatically. The estimator uses

Tests interaction constraints on a synthetic dataset.

Train XGBoost model. .. versionadded:: 1.0.0 .. note:: Other parameters are the same as :py:func:`xgboost.train` except for

split rowset into two

* \brief Obtain the CUDA device ordinal. */

@brief Get const reference to nodes */

* @brief Make a CPU context based on the current context. */

* @brief The number of categories across all features. */

* @brief Get the CUDA device ordinal. -1 if XGBoost is running on CPU. */

* \brief Read the whole buffer from dmlc stream. */

observers

Value

Simple wrapper around testing None.

Validate the gpu parameters and gpu configurations

Get attribute string from the Booster. Parameters ---------- key : The key to get attribute from. Return

Test for one-hot encoding with categorical data.

Check the cut values.

Make cuda array interface str.

Convert array interface to numpy or cupy array

Get attribute value from the Booster based on the key provided. @param key attribute key @return attribute value @throws XGBoostError native error

Get the dump of the model as a string array @param featureMap A string containing the path to a feature map. @param withStats Controls whether the sp

Synthesize a dataset similar to the sklearn California housing dataset. The real one can be obtained via: .. code-block:: import sk

Import pandas with memory cache.

Import pyarrow with memory cache.