C++ API Reference for Intel® Data Analytics Acceleration Library 2020 Update 1

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Parameter Class Reference

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

Class Declaration

class DAAL_EXPORT Parameter
{
public:
Parameter();
size_t maxIterations;
size_t maxTreeDepth;
double shrinkage;
double minSplitLoss;
double lambda;
size_t featuresPerNode;
engines::EnginePtr engine;
size_t maxBins;
size_t minBinSize;
};

Member Data Documentation

engines::EnginePtr engine

Engine for the random numbers generator used by the algorithms

size_t featuresPerNode

Number of features tried as possible splits per node. Range : [0, p] where p is the total number of features. Default is 0 (use all features)

int internalOptions

Internal options

double lambda

L2 regularization parameter on weights. Range: [0, inf). Default is 1

size_t maxBins

Used with 'inexact' split finding method only. Maximal number of discrete bins to bucket continuous features. Default is 256. Increasing the number results in higher computation costs

size_t maxIterations

Maximal number of iterations of the gradient boosted trees training algorithm. Default is 50

size_t maxTreeDepth

Maximal tree depth, 0 for unlimited. Default is 6

bool memorySavingMode

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

size_t minBinSize

Used with 'inexact' split finding method only. Minimal number of observations in a bin. Default is 5

size_t minObservationsInLeafNode

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

double minSplitLoss

Loss regularization parameter. Min loss reduction required to make a further partition on a leaf node of the tree. Range: [0, inf). Default is 0

double observationsPerTreeFraction

Fraction of observations used for a training of one tree, sampling without replacement. Range: (0, 1]. Default is 1 (no sampling, entire dataset is used)

double shrinkage

Learning rate of the boosting procedure. Scales the contribution of each tree by a factor (0, 1]. Default is 0.3

SplitMethod splitMethod

Split finding method. Default is exact


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

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