Package org.opencv.ml
Class NormalBayesClassifier
java.lang.Object
org.opencv.core.Algorithm
org.opencv.ml.StatModel
org.opencv.ml.NormalBayesClassifier
public class NormalBayesClassifier extends StatModel
Bayes classifier for normally distributed data.
SEE: REF: ml_intro_bayes
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Field Summary
Fields inherited from class org.opencv.ml.StatModel
COMPRESSED_INPUT, PREPROCESSED_INPUT, RAW_OUTPUT, UPDATE_MODEL -
Constructor Summary
Constructors Modifier Constructor Description protectedNormalBayesClassifier(long addr) -
Method Summary
Modifier and Type Method Description static NormalBayesClassifier__fromPtr__(long addr)static NormalBayesClassifiercreate()Creates empty model Use StatModel::train to train the model after creation.protected voidfinalize()static NormalBayesClassifierload(String filepath)Loads and creates a serialized NormalBayesClassifier from a file Use NormalBayesClassifier::save to serialize and store an NormalBayesClassifier to disk.static NormalBayesClassifierload(String filepath, String nodeName)Loads and creates a serialized NormalBayesClassifier from a file Use NormalBayesClassifier::save to serialize and store an NormalBayesClassifier to disk.floatpredictProb(Mat inputs, Mat outputs, Mat outputProbs)Predicts the response for sample(s).floatpredictProb(Mat inputs, Mat outputs, Mat outputProbs, int flags)Predicts the response for sample(s).Methods inherited from class org.opencv.ml.StatModel
calcError, empty, getVarCount, isClassifier, isTrained, predict, predict, predict, train, train, trainMethods inherited from class org.opencv.core.Algorithm
clear, getDefaultName, getNativeObjAddr, save
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Constructor Details
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Method Details
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__fromPtr__
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predictProb
Predicts the response for sample(s). The method estimates the most probable classes for input vectors. Input vectors (one or more) are stored as rows of the matrix inputs. In case of multiple input vectors, there should be one output vector outputs. The predicted class for a single input vector is returned by the method. The vector outputProbs contains the output probabilities corresponding to each element of result.- Parameters:
inputs- automatically generatedoutputs- automatically generatedoutputProbs- automatically generatedflags- automatically generated- Returns:
- automatically generated
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predictProb
Predicts the response for sample(s). The method estimates the most probable classes for input vectors. Input vectors (one or more) are stored as rows of the matrix inputs. In case of multiple input vectors, there should be one output vector outputs. The predicted class for a single input vector is returned by the method. The vector outputProbs contains the output probabilities corresponding to each element of result.- Parameters:
inputs- automatically generatedoutputs- automatically generatedoutputProbs- automatically generated- Returns:
- automatically generated
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create
Creates empty model Use StatModel::train to train the model after creation.- Returns:
- automatically generated
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load
Loads and creates a serialized NormalBayesClassifier from a file Use NormalBayesClassifier::save to serialize and store an NormalBayesClassifier to disk. Load the NormalBayesClassifier from this file again, by calling this function with the path to the file. Optionally specify the node for the file containing the classifier- Parameters:
filepath- path to serialized NormalBayesClassifiernodeName- name of node containing the classifier- Returns:
- automatically generated
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load
Loads and creates a serialized NormalBayesClassifier from a file Use NormalBayesClassifier::save to serialize and store an NormalBayesClassifier to disk. Load the NormalBayesClassifier from this file again, by calling this function with the path to the file. Optionally specify the node for the file containing the classifier- Parameters:
filepath- path to serialized NormalBayesClassifier- Returns:
- automatically generated
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finalize
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