TableFixedParameters Class

Definition

Namespace:

Azure.ResourceManager.MachineLearning.Models

Assembly:

Azure.ResourceManager.MachineLearning.dll

Package:

Azure.ResourceManager.MachineLearning v1.2.0-beta.3

Source:

TableFixedParameters.cs

Fixed training parameters that won't be swept over during AutoML Table training.

public class TableFixedParameters

type TableFixedParameters = class

Public Class TableFixedParameters

Inheritance

Object

TableFixedParameters

Constructors

TableFixedParameters()

Initializes a new instance of TableFixedParameters.

Properties

Booster	Specify the boosting type, e.g gbdt for XGBoost.
BoostingType	Specify the boosting type, e.g gbdt for LightGBM.
GrowPolicy	Specify the grow policy, which controls the way new nodes are added to the tree.
LearningRate	The learning rate for the training procedure.
MaxBin	Specify the Maximum number of discrete bins to bucket continuous features .
MaxDepth	Specify the max depth to limit the tree depth explicitly.
MaxLeaves	Specify the max leaves to limit the tree leaves explicitly.
MinDataInLeaf	The minimum number of data per leaf.
MinSplitGain	Minimum loss reduction required to make a further partition on a leaf node of the tree.
ModelName	The name of the model to train.
NEstimators	Specify the number of trees (or rounds) in an model.
NumLeaves	Specify the number of leaves.
PreprocessorName	The name of the preprocessor to use.
RegAlpha	L1 regularization term on weights.
RegLambda	L2 regularization term on weights.
Subsample	Subsample ratio of the training instance.
SubsampleFreq	Frequency of subsample.
TreeMethod	Specify the tree method.
WithMean	If true, center before scaling the data with StandardScalar.
WithStd	If true, scaling the data with Unit Variance with StandardScalar.