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<h2 title="Class NormalBayesClassifier" class="title">Class NormalBayesClassifier</h2>
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<ul class="inheritance">
<li>java.lang.Object</li>
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<li><a href="../../../org/opencv/core/Algorithm.html" title="class in org.opencv.core">org.opencv.core.Algorithm</a></li>
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<li><a href="../../../org/opencv/ml/StatModel.html" title="class in org.opencv.ml">org.opencv.ml.StatModel</a></li>
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<li>org.opencv.ml.NormalBayesClassifier</li>
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<pre>public class <span class="typeNameLabel">NormalBayesClassifier</span>
extends <a href="../../../org/opencv/ml/StatModel.html" title="class in org.opencv.ml">StatModel</a></pre>
<div class="block">Bayes classifier for normally distributed data.

 SEE: REF: ml_intro_bayes</div>
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<code><a href="../../../org/opencv/ml/StatModel.html#COMPRESSED_INPUT">COMPRESSED_INPUT</a>, <a href="../../../org/opencv/ml/StatModel.html#PREPROCESSED_INPUT">PREPROCESSED_INPUT</a>, <a href="../../../org/opencv/ml/StatModel.html#RAW_OUTPUT">RAW_OUTPUT</a>, <a href="../../../org/opencv/ml/StatModel.html#UPDATE_MODEL">UPDATE_MODEL</a></code></li>
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<caption><span id="t0" class="activeTableTab"><span>All Methods</span><span class="tabEnd">&nbsp;</span></span><span id="t1" class="tableTab"><span><a href="javascript:show(1);">Static Methods</a></span><span class="tabEnd">&nbsp;</span></span><span id="t2" class="tableTab"><span><a href="javascript:show(2);">Instance Methods</a></span><span class="tabEnd">&nbsp;</span></span><span id="t4" class="tableTab"><span><a href="javascript:show(8);">Concrete Methods</a></span><span class="tabEnd">&nbsp;</span></span></caption>
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<th class="colFirst" scope="col">Modifier and Type</th>
<th class="colLast" scope="col">Method and Description</th>
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<td class="colFirst"><code>static <a href="../../../org/opencv/ml/NormalBayesClassifier.html" title="class in org.opencv.ml">NormalBayesClassifier</a></code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/ml/NormalBayesClassifier.html#Z:Z__fromPtr__-long-">__fromPtr__</a></span>(long&nbsp;addr)</code>&nbsp;</td>
</tr>
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<td class="colFirst"><code>static <a href="../../../org/opencv/ml/NormalBayesClassifier.html" title="class in org.opencv.ml">NormalBayesClassifier</a></code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/ml/NormalBayesClassifier.html#create--">create</a></span>()</code>
<div class="block">Creates empty model
 Use StatModel::train to train the model after creation.</div>
</td>
</tr>
<tr id="i2" class="altColor">
<td class="colFirst"><code>static <a href="../../../org/opencv/ml/NormalBayesClassifier.html" title="class in org.opencv.ml">NormalBayesClassifier</a></code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/ml/NormalBayesClassifier.html#load-java.lang.String-">load</a></span>(java.lang.String&nbsp;filepath)</code>
<div class="block">Loads and creates a serialized NormalBayesClassifier from a file

 Use NormalBayesClassifier::save to serialize and store an NormalBayesClassifier to disk.</div>
</td>
</tr>
<tr id="i3" class="rowColor">
<td class="colFirst"><code>static <a href="../../../org/opencv/ml/NormalBayesClassifier.html" title="class in org.opencv.ml">NormalBayesClassifier</a></code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/ml/NormalBayesClassifier.html#load-java.lang.String-java.lang.String-">load</a></span>(java.lang.String&nbsp;filepath,
    java.lang.String&nbsp;nodeName)</code>
<div class="block">Loads and creates a serialized NormalBayesClassifier from a file

 Use NormalBayesClassifier::save to serialize and store an NormalBayesClassifier to disk.</div>
</td>
</tr>
<tr id="i4" class="altColor">
<td class="colFirst"><code>float</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/ml/NormalBayesClassifier.html#predictProb-org.opencv.core.Mat-org.opencv.core.Mat-org.opencv.core.Mat-">predictProb</a></span>(<a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;inputs,
           <a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;outputs,
           <a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;outputProbs)</code>
<div class="block">Predicts the response for sample(s).</div>
</td>
</tr>
<tr id="i5" class="rowColor">
<td class="colFirst"><code>float</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/ml/NormalBayesClassifier.html#predictProb-org.opencv.core.Mat-org.opencv.core.Mat-org.opencv.core.Mat-int-">predictProb</a></span>(<a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;inputs,
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           <a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;outputProbs,
           int&nbsp;flags)</code>
<div class="block">Predicts the response for sample(s).</div>
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<h3>Methods inherited from class&nbsp;org.opencv.ml.<a href="../../../org/opencv/ml/StatModel.html" title="class in org.opencv.ml">StatModel</a></h3>
<code><a href="../../../org/opencv/ml/StatModel.html#calcError-org.opencv.ml.TrainData-boolean-org.opencv.core.Mat-">calcError</a>, <a href="../../../org/opencv/ml/StatModel.html#empty--">empty</a>, <a href="../../../org/opencv/ml/StatModel.html#getVarCount--">getVarCount</a>, <a href="../../../org/opencv/ml/StatModel.html#isClassifier--">isClassifier</a>, <a href="../../../org/opencv/ml/StatModel.html#isTrained--">isTrained</a>, <a href="../../../org/opencv/ml/StatModel.html#predict-org.opencv.core.Mat-">predict</a>, <a href="../../../org/opencv/ml/StatModel.html#predict-org.opencv.core.Mat-org.opencv.core.Mat-">predict</a>, <a href="../../../org/opencv/ml/StatModel.html#predict-org.opencv.core.Mat-org.opencv.core.Mat-int-">predict</a>, <a href="../../../org/opencv/ml/StatModel.html#train-org.opencv.core.Mat-int-org.opencv.core.Mat-">train</a>, <a href="../../../org/opencv/ml/StatModel.html#train-org.opencv.ml.TrainData-">train</a>, <a href="../../../org/opencv/ml/StatModel.html#train-org.opencv.ml.TrainData-int-">train</a></code></li>
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<h3>Methods inherited from class&nbsp;org.opencv.core.<a href="../../../org/opencv/core/Algorithm.html" title="class in org.opencv.core">Algorithm</a></h3>
<code><a href="../../../org/opencv/core/Algorithm.html#clear--">clear</a>, <a href="../../../org/opencv/core/Algorithm.html#getDefaultName--">getDefaultName</a>, <a href="../../../org/opencv/core/Algorithm.html#getNativeObjAddr--">getNativeObjAddr</a>, <a href="../../../org/opencv/core/Algorithm.html#save-java.lang.String-">save</a></code></li>
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<h4>__fromPtr__</h4>
<pre>public static&nbsp;<a href="../../../org/opencv/ml/NormalBayesClassifier.html" title="class in org.opencv.ml">NormalBayesClassifier</a>&nbsp;__fromPtr__(long&nbsp;addr)</pre>
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<h4>create</h4>
<pre>public static&nbsp;<a href="../../../org/opencv/ml/NormalBayesClassifier.html" title="class in org.opencv.ml">NormalBayesClassifier</a>&nbsp;create()</pre>
<div class="block">Creates empty model
 Use StatModel::train to train the model after creation.</div>
<dl>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>automatically generated</dd>
</dl>
</li>
</ul>
<a name="load-java.lang.String-">
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<h4>load</h4>
<pre>public static&nbsp;<a href="../../../org/opencv/ml/NormalBayesClassifier.html" title="class in org.opencv.ml">NormalBayesClassifier</a>&nbsp;load(java.lang.String&nbsp;filepath)</pre>
<div class="block">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</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>filepath</code> - path to serialized NormalBayesClassifier</dd>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>automatically generated</dd>
</dl>
</li>
</ul>
<a name="load-java.lang.String-java.lang.String-">
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<h4>load</h4>
<pre>public static&nbsp;<a href="../../../org/opencv/ml/NormalBayesClassifier.html" title="class in org.opencv.ml">NormalBayesClassifier</a>&nbsp;load(java.lang.String&nbsp;filepath,
                                         java.lang.String&nbsp;nodeName)</pre>
<div class="block">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</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>filepath</code> - path to serialized NormalBayesClassifier</dd>
<dd><code>nodeName</code> - name of node containing the classifier</dd>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>automatically generated</dd>
</dl>
</li>
</ul>
<a name="predictProb-org.opencv.core.Mat-org.opencv.core.Mat-org.opencv.core.Mat-">
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<h4>predictProb</h4>
<pre>public&nbsp;float&nbsp;predictProb(<a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;inputs,
                         <a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;outputs,
                         <a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;outputProbs)</pre>
<div class="block">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.</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>inputs</code> - automatically generated</dd>
<dd><code>outputs</code> - automatically generated</dd>
<dd><code>outputProbs</code> - automatically generated</dd>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>automatically generated</dd>
</dl>
</li>
</ul>
<a name="predictProb-org.opencv.core.Mat-org.opencv.core.Mat-org.opencv.core.Mat-int-">
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<h4>predictProb</h4>
<pre>public&nbsp;float&nbsp;predictProb(<a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;inputs,
                         <a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;outputs,
                         <a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;outputProbs,
                         int&nbsp;flags)</pre>
<div class="block">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.</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>inputs</code> - automatically generated</dd>
<dd><code>outputs</code> - automatically generated</dd>
<dd><code>outputProbs</code> - automatically generated</dd>
<dd><code>flags</code> - automatically generated</dd>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>automatically generated</dd>
</dl>
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