Package org.opencv.ml
Class NormalBayesClassifier
- 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.NormalBayesClassifier
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public class NormalBayesClassifier extends StatModel
Bayes classifier for normally distributed data. SEE: REF: ml_intro_bayes
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Field Summary
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Fields inherited from class org.opencv.ml.StatModel
COMPRESSED_INPUT, PREPROCESSED_INPUT, RAW_OUTPUT, UPDATE_MODEL
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Constructor Summary
Constructors Modifier Constructor Description protected
NormalBayesClassifier(long addr)
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description static NormalBayesClassifier
__fromPtr__(long addr)
static NormalBayesClassifier
create()
Creates empty model Use StatModel::train to train the model after creation.protected void
finalize()
static NormalBayesClassifier
load(java.lang.String filepath)
Loads and creates a serialized NormalBayesClassifier from a file Use NormalBayesClassifier::save to serialize and store an NormalBayesClassifier to disk.static NormalBayesClassifier
load(java.lang.String filepath, java.lang.String nodeName)
Loads and creates a serialized NormalBayesClassifier from a file Use NormalBayesClassifier::save to serialize and store an NormalBayesClassifier to disk.float
predictProb(Mat inputs, Mat outputs, Mat outputProbs)
Predicts the response for sample(s).float
predictProb(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, train
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Methods inherited from class org.opencv.core.Algorithm
clear, getDefaultName, getNativeObjAddr, save
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Method Detail
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__fromPtr__
public static NormalBayesClassifier __fromPtr__(long addr)
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predictProb
public float predictProb(Mat inputs, Mat outputs, Mat outputProbs, int flags)
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
public float predictProb(Mat inputs, Mat outputs, Mat outputProbs)
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
public static NormalBayesClassifier create()
Creates empty model Use StatModel::train to train the model after creation.- Returns:
- automatically generated
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load
public static NormalBayesClassifier load(java.lang.String filepath, java.lang.String nodeName)
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
public static NormalBayesClassifier load(java.lang.String filepath)
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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