secretflow.ml.boost.sgb_v.factory.components.tree_trainer#

Classes:

`TreeTrainer`()
`LevelWiseTreeTrainer`()

class secretflow.ml.boost.sgb_v.factory.components.tree_trainer.TreeTrainer[源代码]#

基类：Composite

Methods:

`show_params`()
`set_params`(params)
`set_devices`(devices)
`train_tree`(cur_tree_num, order_map_manager, ...)	train on training data

show_params()[源代码]#

set_params(params: dict)[源代码]#

set_devices(devices: Devices)[源代码]#

abstract train_tree(cur_tree_num, order_map_manager, y, pred, x_shape) → DistributedTree[源代码]#: train on training data

class secretflow.ml.boost.sgb_v.factory.components.tree_trainer.LevelWiseTreeTrainer[源代码]#

基类：TreeTrainer

Methods:

`__init__`()
`show_params`()
`set_params`(params)
`get_params`(params)
`set_devices`(devices)
`train_tree`(cur_tree_num, order_map_manager, ...)	train on training data

__init__() → None[源代码]#

show_params()[源代码]#

set_params(params: dict)[源代码]#

get_params(params: dict)[源代码]#

set_devices(devices: Devices)[源代码]#

train_tree(cur_tree_num, order_map_manager: OrderMapManager, y: PYUObject, pred: Union[PYUObject, ndarray], x_shape: Tuple[int, int]) → DistributedTree[源代码]#: train on training data

secretflow.ml.boost.sgb_v.factory.components.tree_trainer.level_wise_tree_trainer#

Classes:

`LevelWiseTreeTrainerComponents`(leaf_manager, ...)
`LevelWiseTreeTrainerParams`([max_depth])	params specifically belonged to level wise booster, not its components.
`LevelWiseTreeTrainer`()

class secretflow.ml.boost.sgb_v.factory.components.tree_trainer.level_wise_tree_trainer.LevelWiseTreeTrainerComponents(leaf_manager: secretflow.ml.boost.sgb_v.factory.components.leaf_manager.leaf_manager.LeafManager = <secretflow.ml.boost.sgb_v.factory.components.leaf_manager.leaf_manager.LeafManager object at 0x7f5e4f098a30>, node_selector: secretflow.ml.boost.sgb_v.factory.components.node_selector.node_selector.NodeSelector = <secretflow.ml.boost.sgb_v.factory.components.node_selector.node_selector.NodeSelector object at 0x7f5e4f0a37c0>, sampler: secretflow.ml.boost.sgb_v.factory.components.sampler.sampler.Sampler = <secretflow.ml.boost.sgb_v.factory.components.sampler.sampler.Sampler object at 0x7f5e4f0ac7c0>, shuffler: secretflow.ml.boost.sgb_v.factory.components.shuffler.shuffler.Shuffler = <secretflow.ml.boost.sgb_v.factory.components.shuffler.shuffler.Shuffler object at 0x7f5e4f0b3a30>, gradient_encryptor: secretflow.ml.boost.sgb_v.factory.components.gradient_encryptor.gradient_encryptor.GradientEncryptor = <secretflow.ml.boost.sgb_v.factory.components.gradient_encryptor.gradient_encryptor.GradientEncryptor object at 0x7f5e4f0b3cd0>, loss_computer: secretflow.ml.boost.sgb_v.factory.components.loss_computer.loss_computer.LossComputer = <secretflow.ml.boost.sgb_v.factory.components.loss_computer.loss_computer.LossComputer object at 0x7f5e4f1469a0>, bucket_sum_calculator: secretflow.ml.boost.sgb_v.factory.components.bucket_sum_calculator.bucket_sum_calculator.BucketSumCalculator = <secretflow.ml.boost.sgb_v.factory.components.bucket_sum_calculator.bucket_sum_calculator.BucketSumCalculator object at 0x7f5e4f146a90>, split_finder: secretflow.ml.boost.sgb_v.factory.components.split_finder.split_finder.SplitFinder = <secretflow.ml.boost.sgb_v.factory.components.split_finder.split_finder.SplitFinder object at 0x7f5e4f146b20>, split_tree_builder: secretflow.ml.boost.sgb_v.factory.components.split_tree_builder.split_tree_builder.SplitTreeBuilder = <secretflow.ml.boost.sgb_v.factory.components.split_tree_builder.split_tree_builder.SplitTreeBuilder object at 0x7f5e4f146be0>)[源代码]#

基类：object

Attributes:

`leaf_manager`
`node_selector`
`sampler`
`shuffler`
`gradient_encryptor`
`loss_computer`
`bucket_sum_calculator`
`split_finder`
`split_tree_builder`

Methods:

__init__([leaf_manager, node_selector, ...])

leaf_manager: LeafManager = <secretflow.ml.boost.sgb_v.factory.components.leaf_manager.leaf_manager.LeafManager object>#

node_selector: NodeSelector = <secretflow.ml.boost.sgb_v.factory.components.node_selector.node_selector.NodeSelector object>#

sampler: Sampler = <secretflow.ml.boost.sgb_v.factory.components.sampler.sampler.Sampler object>#

shuffler: Shuffler = <secretflow.ml.boost.sgb_v.factory.components.shuffler.shuffler.Shuffler object>#

gradient_encryptor: GradientEncryptor = <secretflow.ml.boost.sgb_v.factory.components.gradient_encryptor.gradient_encryptor.GradientEncryptor object>#

loss_computer: LossComputer = <secretflow.ml.boost.sgb_v.factory.components.loss_computer.loss_computer.LossComputer object>#

bucket_sum_calculator: BucketSumCalculator = <secretflow.ml.boost.sgb_v.factory.components.bucket_sum_calculator.bucket_sum_calculator.BucketSumCalculator object>#

split_finder: SplitFinder = <secretflow.ml.boost.sgb_v.factory.components.split_finder.split_finder.SplitFinder object>#

split_tree_builder: SplitTreeBuilder = <secretflow.ml.boost.sgb_v.factory.components.split_tree_builder.split_tree_builder.SplitTreeBuilder object>#

__init__(leaf_manager: ~secretflow.ml.boost.sgb_v.factory.components.leaf_manager.leaf_manager.LeafManager = <secretflow.ml.boost.sgb_v.factory.components.leaf_manager.leaf_manager.LeafManager object>, node_selector: ~secretflow.ml.boost.sgb_v.factory.components.node_selector.node_selector.NodeSelector = <secretflow.ml.boost.sgb_v.factory.components.node_selector.node_selector.NodeSelector object>, sampler: ~secretflow.ml.boost.sgb_v.factory.components.sampler.sampler.Sampler = <secretflow.ml.boost.sgb_v.factory.components.sampler.sampler.Sampler object>, shuffler: ~secretflow.ml.boost.sgb_v.factory.components.shuffler.shuffler.Shuffler = <secretflow.ml.boost.sgb_v.factory.components.shuffler.shuffler.Shuffler object>, gradient_encryptor: ~secretflow.ml.boost.sgb_v.factory.components.gradient_encryptor.gradient_encryptor.GradientEncryptor = <secretflow.ml.boost.sgb_v.factory.components.gradient_encryptor.gradient_encryptor.GradientEncryptor object>, loss_computer: ~secretflow.ml.boost.sgb_v.factory.components.loss_computer.loss_computer.LossComputer = <secretflow.ml.boost.sgb_v.factory.components.loss_computer.loss_computer.LossComputer object>, bucket_sum_calculator: ~secretflow.ml.boost.sgb_v.factory.components.bucket_sum_calculator.bucket_sum_calculator.BucketSumCalculator = <secretflow.ml.boost.sgb_v.factory.components.bucket_sum_calculator.bucket_sum_calculator.BucketSumCalculator object>, split_finder: ~secretflow.ml.boost.sgb_v.factory.components.split_finder.split_finder.SplitFinder = <secretflow.ml.boost.sgb_v.factory.components.split_finder.split_finder.SplitFinder object>, split_tree_builder: ~secretflow.ml.boost.sgb_v.factory.components.split_tree_builder.split_tree_builder.SplitTreeBuilder = <secretflow.ml.boost.sgb_v.factory.components.split_tree_builder.split_tree_builder.SplitTreeBuilder object>) → None#

class secretflow.ml.boost.sgb_v.factory.components.tree_trainer.level_wise_tree_trainer.LevelWiseTreeTrainerParams(max_depth: int = 5)[源代码]#

基类：object

params specifically belonged to level wise booster, not its components.

‘max_depth’: int, maximum depth of a tree.: default: 5 range: [1, 16]

Attributes:

max_depth

Methods:

__init__([max_depth])

max_depth: int = 5#

__init__(max_depth: int = 5) → None#

class secretflow.ml.boost.sgb_v.factory.components.tree_trainer.level_wise_tree_trainer.LevelWiseTreeTrainer[源代码]#

基类：TreeTrainer

Methods:

`__init__`()
`show_params`()
`set_params`(params)
`get_params`(params)
`set_devices`(devices)
`train_tree`(cur_tree_num, order_map_manager, ...)	train on training data

__init__() → None[源代码]#

show_params()[源代码]#

set_params(params: dict)[源代码]#

get_params(params: dict)[源代码]#

set_devices(devices: Devices)[源代码]#

train_tree(cur_tree_num, order_map_manager: OrderMapManager, y: PYUObject, pred: Union[PYUObject, ndarray], x_shape: Tuple[int, int]) → DistributedTree[源代码]#: train on training data

secretflow.ml.boost.sgb_v.factory.components.tree_trainer.tree_trainer#

Classes:

TreeTrainer()

class secretflow.ml.boost.sgb_v.factory.components.tree_trainer.tree_trainer.TreeTrainer[源代码]#

基类：Composite

Methods:

`show_params`()
`set_params`(params)
`set_devices`(devices)
`train_tree`(cur_tree_num, order_map_manager, ...)	train on training data

show_params()[源代码]#

set_params(params: dict)[源代码]#

set_devices(devices: Devices)[源代码]#

abstract train_tree(cur_tree_num, order_map_manager, y, pred, x_shape) → DistributedTree[源代码]#: train on training data