Table of Contents

Class DTrees

Namespace
Emgu.CV.ML
Assembly
Emgu.CV.dll

Decision Trees

public class DTrees : UnmanagedObject, IDisposable, IStatModel, IAlgorithm
Inheritance
DTrees
Implements
Inherited Members
Extension Methods

Constructors

DTrees()

Create a default decision tree

public DTrees()

Properties

CVFolds

If CVFolds greater than 1 then algorithms prunes the built decision tree using K-fold

public int CVFolds { get; set; }

Property Value

int

MaxCategories

Cluster possible values of a categorical variable into K less than or equals maxCategories clusters to find a suboptimal split

public int MaxCategories { get; set; }

Property Value

int

MaxDepth

The maximum possible depth of the tree

public int MaxDepth { get; set; }

Property Value

int

MinSampleCount

If the number of samples in a node is less than this parameter then the node will not be split

public int MinSampleCount { get; set; }

Property Value

int

RegressionAccuracy

Termination criteria for regression trees

public float RegressionAccuracy { get; set; }

Property Value

float

TruncatePrunedTree

If true then pruned branches are physically removed from the tree

public bool TruncatePrunedTree { get; set; }

Property Value

bool

Use1SERule

If true then a pruning will be harsher

public bool Use1SERule { get; set; }

Property Value

bool

UseSurrogates

If true then surrogate splits will be built

public bool UseSurrogates { get; set; }

Property Value

bool

Methods

DisposeObject()

Release the decision tree and all the memory associate with it

protected override void DisposeObject()