🤖 AIによる機械翻訳(非公式) — これは OpenCV 5.0.0 公式リファレンス(英語)を AI (Claude) で自動翻訳したものです。訳に誤りを含む場合があります。正確な情報は 公式英語版(原文) を参照してください。
Package org.opencv.ml
クラス DTrees
- java.lang.Object
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- org.opencv.core.Algorithm
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- org.opencv.ml.StatModel
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- org.opencv.ml.DTrees
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public class DTrees extends StatModel
The class represents a single decision tree or a collection of decision trees. The current public interface of the class allows user to train only a single decision tree, however the class is capable of storing multiple decision trees and using them for prediction (by summing responses or using a voting schemes), and the derived from DTrees classes (such as RTrees and Boost) use this capability to implement decision tree ensembles. SEE: REF: ml_intro_trees
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フィールドの要約
フィールド Modifier and Type Field Description static intPREDICT_AUTOstatic intPREDICT_MASKstatic intPREDICT_MAX_VOTEstatic intPREDICT_SUM-
クラス org.opencv.ml.StatModel から継承されたフィールド
COMPRESSED_INPUT, PREPROCESSED_INPUT, RAW_OUTPUT, UPDATE_MODEL
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コンストラクタの要約
コンストラクタ Modifier Constructor Description protectedDTrees​(long addr)
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メソッドの要約
すべてのメソッド 静的メソッド インスタンスメソッド 具象メソッド Modifier and Type Method Description static DTrees__fromPtr__​(long addr)static DTreescreate()Creates the empty model The static method creates empty decision tree with the specified parameters.intgetCVFolds()SEE: setCVFoldsintgetMaxCategories()SEE: setMaxCategoriesintgetMaxDepth()SEE: setMaxDepthintgetMinSampleCount()SEE: setMinSampleCountMatgetPriors()SEE: setPriorsfloatgetRegressionAccuracy()SEE: setRegressionAccuracybooleangetTruncatePrunedTree()SEE: setTruncatePrunedTreebooleangetUse1SERule()SEE: setUse1SERulebooleangetUseSurrogates()SEE: setUseSurrogatesstatic DTreesload​(java.lang.String filepath)Loads and creates a serialized DTrees from a file Use DTree::save to serialize and store an DTree to disk.static DTreesload​(java.lang.String filepath, java.lang.String nodeName)Loads and creates a serialized DTrees from a file Use DTree::save to serialize and store an DTree to disk.voidsetCVFolds​(int val)getCVFolds SEE: getCVFoldsvoidsetMaxCategories​(int val)getMaxCategories SEE: getMaxCategoriesvoidsetMaxDepth​(int val)getMaxDepth SEE: getMaxDepthvoidsetMinSampleCount​(int val)getMinSampleCount SEE: getMinSampleCountvoidsetPriors​(Mat val)getPriors SEE: getPriorsvoidsetRegressionAccuracy​(float val)getRegressionAccuracy SEE: getRegressionAccuracyvoidsetTruncatePrunedTree​(boolean val)getTruncatePrunedTree SEE: getTruncatePrunedTreevoidsetUse1SERule​(boolean val)getUse1SERule SEE: getUse1SERulevoidsetUseSurrogates​(boolean val)getUseSurrogates SEE: getUseSurrogates-
クラス org.opencv.ml.StatModel から継承されたメソッド
calcError, empty, getVarCount, isClassifier, isTrained, predict, predict, predict, train, train, train
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クラス org.opencv.core.Algorithm から継承されたメソッド
clear, getDefaultName, getNativeObjAddr, save
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メソッドの詳細
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__fromPtr__
public static DTrees __fromPtr__​(long addr)
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getMaxCategories
public int getMaxCategories()
SEE: setMaxCategories- 戻り値:
- 自動生成
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setMaxCategories
public void setMaxCategories​(int val)
getMaxCategories SEE: getMaxCategories- 引数:
val- 自動生成
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getMaxDepth
public int getMaxDepth()
SEE: setMaxDepth- 戻り値:
- 自動生成
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setMaxDepth
public void setMaxDepth​(int val)
getMaxDepth SEE: getMaxDepth- 引数:
val- 自動生成
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getMinSampleCount
public int getMinSampleCount()
SEE: setMinSampleCount- 戻り値:
- 自動生成
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setMinSampleCount
public void setMinSampleCount​(int val)
getMinSampleCount SEE: getMinSampleCount- 引数:
val- 自動生成
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getCVFolds
public int getCVFolds()
SEE: setCVFolds- 戻り値:
- 自動生成
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setCVFolds
public void setCVFolds​(int val)
getCVFolds SEE: getCVFolds- 引数:
val- 自動生成
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getUseSurrogates
public boolean getUseSurrogates()
SEE: setUseSurrogates- 戻り値:
- 自動生成
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setUseSurrogates
public void setUseSurrogates​(boolean val)
getUseSurrogates SEE: getUseSurrogates- 引数:
val- 自動生成
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getUse1SERule
public boolean getUse1SERule()
SEE: setUse1SERule- 戻り値:
- 自動生成
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setUse1SERule
public void setUse1SERule​(boolean val)
getUse1SERule SEE: getUse1SERule- 引数:
val- 自動生成
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getTruncatePrunedTree
public boolean getTruncatePrunedTree()
SEE: setTruncatePrunedTree- 戻り値:
- 自動生成
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setTruncatePrunedTree
public void setTruncatePrunedTree​(boolean val)
getTruncatePrunedTree SEE: getTruncatePrunedTree- 引数:
val- 自動生成
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getRegressionAccuracy
public float getRegressionAccuracy()
SEE: setRegressionAccuracy- 戻り値:
- 自動生成
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setRegressionAccuracy
public void setRegressionAccuracy​(float val)
getRegressionAccuracy SEE: getRegressionAccuracy- 引数:
val- 自動生成
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getPriors
public Mat getPriors()
SEE: setPriors- 戻り値:
- 自動生成
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setPriors
public void setPriors​(Mat val)
getPriors SEE: getPriors- 引数:
val- 自動生成
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create
public static DTrees create()
Creates the empty model The static method creates empty decision tree with the specified parameters. It should be then trained using train method (see StatModel::train). Alternatively, you can load the model from file using Algorithm::load<DTrees>(filename).- 戻り値:
- 自動生成
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load
public static DTrees load​(java.lang.String filepath, java.lang.String nodeName)
Loads and creates a serialized DTrees from a file Use DTree::save to serialize and store an DTree to disk. Load the DTree from this file again, by calling this function with the path to the file. Optionally specify the node for the file containing the classifier- 引数:
filepath- シリアライズされたDTreeへのパスnodeName- 分類器を含むノードの名前- 戻り値:
- 自動生成
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load
public static DTrees load​(java.lang.String filepath)
Loads and creates a serialized DTrees from a file Use DTree::save to serialize and store an DTree to disk. Load the DTree from this file again, by calling this function with the path to the file. Optionally specify the node for the file containing the classifier- 引数:
filepath- シリアライズされたDTreeへのパス- 戻り値:
- 自動生成
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