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OpenCV 2.4.7 | |||||||
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java.lang.Objectorg.opencv.ml.CvDTreeParams
org.opencv.ml.CvBoostParams
public class CvBoostParams
Boosting training parameters.
There is one structure member that you can set directly:
Splitting criteria used to choose optimal splits during a weak tree construction. Possible values are:
// C++ code:
The structure is derived from "CvDTreeParams" but not all of the decision tree parameters are supported. In particular, cross-validation is not supported.
All parameters are public. You can initialize them by a constructor and then override some of them directly if you want.
| Constructor Summary | |
|---|---|
CvBoostParams()
The constructors.  | 
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| Method Summary | |
|---|---|
 int | 
get_boost_type()
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 int | 
get_split_criteria()
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 int | 
get_weak_count()
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 double | 
get_weight_trim_rate()
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 void | 
set_boost_type(int boost_type)
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 void | 
set_split_criteria(int split_criteria)
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 void | 
set_weak_count(int weak_count)
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 void | 
set_weight_trim_rate(double weight_trim_rate)
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| Methods inherited from class java.lang.Object | 
|---|
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait | 
| Constructor Detail | 
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public CvBoostParams()
The constructors.
See "CvDTreeParams.CvDTreeParams" for description of other parameters.
Default parameters are:
// C++ code:
CvBoostParams.CvBoostParams()
boost_type = CvBoost.REAL;
weak_count = 100;
weight_trim_rate = 0.95;
cv_folds = 0;
max_depth = 1;
| Method Detail | 
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public int get_boost_type()
public int get_split_criteria()
public int get_weak_count()
public double get_weight_trim_rate()
public void set_boost_type(int boost_type)
public void set_split_criteria(int split_criteria)
public void set_weak_count(int weak_count)
public void set_weight_trim_rate(double weight_trim_rate)
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