xgboost.spark.params.HasEnableSparseDataOptim Class Reference

Inheritance diagram for xgboost.spark.params.HasEnableSparseDataOptim:

Public Member Functions
None	__init__ (self)

Static Public Attributes
	enable_sparse_data_optim

Detailed Description

This is a Params based class that is extended by _SparkXGBParams
and holds the variable to store the boolean config of enabling sparse data optimization.

Field Documentation

enable_sparse_data_optim

xgboost.spark.params.HasEnableSparseDataOptim.enable_sparse_data_optim

static

Initial value:

=  Param(
        Params._dummy(),
        "enable_sparse_data_optim",
        "This stores the boolean config of enabling sparse data optimization, if enabled, "
        "Xgboost DMatrix object will be constructed from sparse matrix instead of "
        "dense matrix. This config is disabled by default. If most of examples in your "
        "training dataset contains sparse features, we suggest to enable this config.",
        typeConverter=TypeConverters.toBoolean,
    )

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The documentation for this class was generated from the following file:

• External/xgboost/python-package/xgboost/spark/params.py