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 decision forest algorithm. More...

Public Member Functions

def __init__
 

Static Public Attributes

 nTrees = ...
 
 observationsPerTreeFraction = ...
 
 featuresPerNode = ...
 
 maxTreeDepth = ...
 
 minObservationsInLeafNode = ...
 
 seed = ...
 
 engine = ...
 
 impurityThreshold = ...
 
 varImportance = ...
 
 resultsToCompute = ...
 
 memorySavingMode = ...
 
 bootstrap = ...
 

Detailed Description

Constructor & Destructor Documentation

def __init__ (   self)

Member Data Documentation

bootstrap = ...
static

If true then training set for a tree is a bootstrap of the whole training set

engine = ...
static

Engine for the random numbers generator used by the algorithms

featuresPerNode = ...
static

Number of features tried as possible splits per node.

impurityThreshold = ...
static

Threshold value used as stopping criteria: if the impurity value in the node is smaller

maxTreeDepth = ...
static

Maximal tree depth. Default is 0 (unlimited)

memorySavingMode = ...
static

If true then use memory saving (but slower) mode

minObservationsInLeafNode = ...
static

Minimal number of observations in a leaf node.

nTrees = ...
static

Number of trees in the forest. Default is 10

observationsPerTreeFraction = ...
static

Fraction of observations used for a training of one tree, 0 to 1.

resultsToCompute = ...
static

64 bit integer flag that indicates the results to compute

seed = ...
static

Seed for the random numbers generator used by the algorithms

Deprecated:
This item will be removed in a future release.

Use engine instead.

varImportance = ...
static

Variable importance computation mode


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

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