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Merge branch '2.4'
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@@ -169,11 +169,11 @@ CvBoost::predict
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----------------
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Predicts a response for an input sample.
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.. ocv:function:: float CvBoost::predict( const Mat& sample, const Mat& missing=Mat(), const Range& slice=Range::all(), bool raw_mode=false, bool return_sum=false ) const
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.. ocv:function:: float CvBoost::predict( const cv::Mat& sample, const cv::Mat& missing=Mat(), const cv::Range& slice=Range::all(), bool rawMode=false, bool returnSum=false ) const
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.. ocv:function:: float CvBoost::predict( const CvMat* sample, const CvMat* missing=0, CvMat* weak_responses=0, CvSlice slice=CV_WHOLE_SEQ, bool raw_mode=false, bool return_sum=false ) const
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.. ocv:pyfunction:: cv2.Boost.predict(sample[, missing[, slice[, raw_mode[, return_sum]]]]) -> retval
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.. ocv:pyfunction:: cv2.Boost.predict(sample[, missing[, slice[, rawMode[, returnSum]]]]) -> retval
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:param sample: Input sample.
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@@ -183,9 +183,9 @@ Predicts a response for an input sample.
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:param slice: Continuous subset of the sequence of weak classifiers to be used for prediction. By default, all the weak classifiers are used.
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:param raw_mode: Normally, it should be set to ``false``.
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:param rawMode: Normally, it should be set to ``false``.
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:param return_sum: If ``true`` then return sum of votes instead of the class label.
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:param returnSum: If ``true`` then return sum of votes instead of the class label.
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The method runs the sample through the trees in the ensemble and returns the output class label based on the weighted voting.
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@@ -232,6 +232,8 @@ Predicts the response for input sample(s).
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.. ocv:pyfunction:: cv2.SVM.predict(sample[, returnDFVal]) -> retval
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.. ocv:pyfunction:: cv2.SVM.predict_all(samples[, results]) -> results
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:param sample: Input sample for prediction.
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:param samples: Input samples for prediction.
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