Set init score of Booster to start from. Parameters ---------- init_score : list, numpy array or None Init score

! * \brief Set splittable to this histogram */

given a real threshold, find the closest threshold bin

! * \brief Get index of label column * \return index of label column */

exception handle and error msg

! * \brief Generate random integer, int32 range * \param lower_bound lower bound * \param upper_bound upper bound * \return The random integer

! * \brief Get number of classes * \return Number of classes */

! * \brief Read part of text data from file in memory, use filter_fun to filter data * \param filter_fun Function that perform data filter * \pa

Computes the (negative) entropy for label p; p should be in interval [0, 1]; This is used to presum the KL-divergence offset term (to be _added_ to th

Get inner evaluation count and names

Initialize data from a CSR matrix.

Predict for training and validation dataset

Predict for a csr data

Predict for a 2-D numpy matrix.

[Private] Load model from string

return number of arguments of a function

consume_garbage() * * Advance until the current character is non-whitespace and non-comment. */

fix the memory of multi-dimensional sliced object

Dump Booster to json format. Parameters ---------- num_iteration: int, optional (default=-1) Index of the iterati

Evaluate for training data. Parameters ---------- feval : callable or None, optional (default=None) Custom evalua

Free Booster's Datasets.

Get a chain of Dataset objects, starting with r, then going to r.reference if exists, then to r.reference.reference, etc. until we hit ``ref_l

internal function

Check is a number or not, include numpy number etc.

! \brief Get the index of label column */

Get the number of columns (features) in the Dataset. Returns ------- number_of_columns : int The number of column

Get number of features. Returns ------- num_feature : int The number of features.

parse_json() * * Parse a JSON object. */