Python* API Reference for Intel® Data Analytics Acceleration Library 2020 Update 1

Public Member Functions | Static Public Attributes | List of all members
Parameter Class Reference

Parameters for the gradient boosted trees algorithm. More...

Public Member Functions

def __init__
 

Static Public Attributes

 splitMethod = ...
 
 maxIterations = ...
 
 maxTreeDepth = ...
 
 shrinkage = ...
 
 minSplitLoss = ...
 
 observationsPerTreeFraction = ...
 
 featuresPerNode = ...
 
 minObservationsInLeafNode = ...
 
 memorySavingMode = ...
 
 engine = ...
 
 maxBins = ...
 
 minBinSize = ...
 
 internalOptions = ...
 

Detailed Description

Constructor & Destructor Documentation

def __init__ (   self)

Member Data Documentation

engine = ...
static

Engine for the random numbers generator used by the algorithms

featuresPerNode = ...
static

Number of features tried as possible splits per node.

internalOptions = ...
static

Internal options

maxBins = ...
static

Used with 'inexact' split finding method only.

maxIterations = ...
static

Maximal number of iterations of the gradient boosted trees training algorithm.

maxTreeDepth = ...
static

Maximal tree depth, 0 for unlimited. Default is 6

memorySavingMode = ...
static

If true then use memory saving (but slower) mode. Default is false

minBinSize = ...
static

Used with 'inexact' split finding method only.

minObservationsInLeafNode = ...
static

Minimal number of observations in a leaf node. Default is 5.

minSplitLoss = ...
static

Loss regularization parameter. Min loss reduction required to make a further partition

observationsPerTreeFraction = ...
static

Fraction of observations used for a training of one tree, sampling without replacement.

shrinkage = ...
static

Learning rate of the boosting procedure.

splitMethod = ...
static

Split finding method. Default is exact


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

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