All Classes and Interfaces
Class
Description
Off-heap implementation of a Dense Matrix, matrix size is only limited by the
amount of the available memory and the matrix dimension cannot exceed
Integer.MAX_VALUE (this is consistent with XGBoost API restrictions on maximum
length of a response).
Booster for xgboost, this is a model API that support interactive build of an XGBoost Model
Supported feature importance types
WEIGHT = Number of nodes that a feature was used to determine a split
GAIN = Average information gain per split for a feature
COVER = Average cover per split for a feature
TOTAL_GAIN = Total information gain over all splits of a feature
TOTAL_COVER = Total cover over all splits of a feature
This enumeration defines the type of prediction to be made and is used for inplace predictions.
This Column abstraction provides an array interface JSON string, which is
used to reconstruct columnar data within the XGBoost library.
This class wraps multiple Column and provides the array interface json
for all columns.
Collective communicator global class for synchronization.
Global configuration context for XGBoost.
DMatrix for xgboost.
sparse matrix type (CSR or CSC)
This class contains the methods that are required for managing the state of the training
process.
interface for customized evaluation
interface for customize Object function
Interface for a tracker implementations with three public methods:
- start(timeout): Start the tracker awaiting for worker connections, with a given
timeout value (in seconds)
Labeled training data point.
Java implementation of the Rabit tracker to coordinate distributed workers.
Simple class to obtain access to the
Unsafe object.trainer for xgboost
custom error class for xgboost
xgboost JNI functions
change 2015-7-6: *use a long[] (length=1) as container of handle to get the
output DMatrix or Booster