Class NormalBayesClassifier

Bayes classifier for normally distributed data

Inheritance
System.Object
DisposableObject
DisposableCvObject
Algorithm
StatModel
NormalBayesClassifier
Implements
Inherited Members
Namespace: OpenCvSharp.ML
Assembly: OpenCvSharp.dll
Syntax
public class NormalBayesClassifier : StatModel, ICvPtrHolder

Constructors

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NormalBayesClassifier(IntPtr)

Creates instance by raw pointer cv::ml::NormalBayesClassifier*

Declaration
protected NormalBayesClassifier(IntPtr p)
Parameters
Type Name Description
IntPtr p

Methods

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Create()

Creates empty model. Use StatModel::train to train the model after creation.

Declaration
public static NormalBayesClassifier Create()
Returns
Type Description
NormalBayesClassifier
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DisposeManaged()

Releases managed resources

Declaration
protected override void DisposeManaged()
Overrides
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DisposeUnmanaged()

Declaration
protected override void DisposeUnmanaged()
Overrides
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Get()

Declaration
public override IntPtr Get()
Returns
Type Description
IntPtr
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Load(String)

Loads and creates a serialized model from a file.

Declaration
public static NormalBayesClassifier Load(string filePath)
Parameters
Type Name Description
System.String filePath
Returns
Type Description
NormalBayesClassifier
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LoadFromString(String)

Loads algorithm from a String.

Declaration
public static NormalBayesClassifier LoadFromString(string strModel)
Parameters
Type Name Description
System.String strModel

he string variable containing the model you want to load.
Returns
Type Description
NormalBayesClassifier
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PredictProb(InputArray, OutputArray, OutputArray, Int32)

Predicts the response for sample(s).

Declaration
public float PredictProb(InputArray inputs, OutputArray outputs, OutputArray outputProbs, int flags = 0)
Parameters
Type Name Description
InputArray inputs
OutputArray outputs
OutputArray outputProbs
System.Int32 flags
Returns
Type Description
System.Single
Remarks

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.

Implements