org.bytedeco.javacpp

Class opencv_ml.DTrees.Split

java.lang.Object

org.bytedeco.javacpp.Pointer

org.bytedeco.javacpp.opencv_ml.DTrees.Split

All Implemented Interfaces:

AutoCloseable

Enclosing class:

opencv_ml.DTrees

@NoOffset
public static class opencv_ml.DTrees.Split
extends Pointer

\brief The class represents split in a decision tree.

Nested Class Summary

Nested classes/interfaces inherited from class org.bytedeco.javacpp.Pointer

Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator

Field Summary

Fields inherited from class org.bytedeco.javacpp.Pointer

address, capacity, limit, position

Constructor Summary

Constructors

Constructor and Description
opencv_ml.DTrees.Split()
opencv_ml.DTrees.Split(long size) Native array allocator.
opencv_ml.DTrees.Split(Pointer p) Pointer cast constructor.

Method Summary

Methods

Modifier and Type	Method and Description
float	c() The threshold value in case of split on an ordered variable.
opencv_ml.DTrees.Split	c(float c)
boolean	inversed() If true, then the inverse split rule is used (i.e.
opencv_ml.DTrees.Split	inversed(boolean inversed)
int	next() Index of the next split in the list of splits for the node
opencv_ml.DTrees.Split	next(int next)
opencv_ml.DTrees.Split	position(long position)
float	quality() The split quality, a positive number.
opencv_ml.DTrees.Split	quality(float quality)
int	subsetOfs() Offset of the bitset used by the split on a categorical variable.
opencv_ml.DTrees.Split	subsetOfs(int subsetOfs)
int	varIdx() Index of variable on which the split is created.
opencv_ml.DTrees.Split	varIdx(int varIdx)

Methods inherited from class org.bytedeco.javacpp.Pointer

address, asBuffer, asByteBuffer, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, hashCode, isNull, limit, limit, maxBytes, memchr, memcmp, memcpy, memmove, memset, offsetof, position, put, setNull, sizeof, toString, totalBytes, withDeallocator, zero

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

opencv_ml.DTrees.Split

public opencv_ml.DTrees.Split(Pointer p)

Pointer cast constructor. Invokes Pointer.Pointer(Pointer).

opencv_ml.DTrees.Split

public opencv_ml.DTrees.Split(long size)

Native array allocator. Access with Pointer.position(long).

opencv_ml.DTrees.Split

public opencv_ml.DTrees.Split()

Method Detail

position

public opencv_ml.DTrees.Split position(long position)

Overrides:

position in class Pointer

varIdx

public int varIdx()

Index of variable on which the split is created.

varIdx

public opencv_ml.DTrees.Split varIdx(int varIdx)

inversed

@Cast(value="bool")
public boolean inversed()

If true, then the inverse split rule is used (i.e. left and right branches are exchanged in the rule expressions below).

inversed

public opencv_ml.DTrees.Split inversed(boolean inversed)

quality

public float quality()

The split quality, a positive number. It is used to choose the best split.

quality

public opencv_ml.DTrees.Split quality(float quality)

next

public int next()

Index of the next split in the list of splits for the node

next

public opencv_ml.DTrees.Split next(int next)

c

public float c()

The threshold value in case of split on an ordered variable. The rule is:

{.none}
                              if var_value < c
                                then next_node <- left
                                else next_node <- right
                              

c

public opencv_ml.DTrees.Split c(float c)

subsetOfs

public int subsetOfs()

Offset of the bitset used by the split on a categorical variable. The rule is:

{.none}
                                    if bitset[var_value] == 1
                                        then next_node <- left
                                        else next_node <- right
                                    

subsetOfs

public opencv_ml.DTrees.Split subsetOfs(int subsetOfs)