C++ API Reference for Intel® Data Analytics Acceleration Library 2018 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;
};

Member Data Documentation

double approxSplitAccuracy

Used with 'approximate' split finding method only. O(1/approxSplitAccuracy) is an estimate for a number of bins Range (0, 1). Default is 0.03

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 'histogramm' split finding method only. Maximal number of discrete bins to bucket continuous features. Default is 256. Increasing the number results in the higher the 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 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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