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TableFixedParameters Class

Definition

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

public class TableFixedParameters
type TableFixedParameters = class
Public Class TableFixedParameters
Inheritance
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.

Applies to