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@@ -318,4 +318,3 @@ decision tree.
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.. [Breiman84] Breiman, L., Friedman, J. Olshen, R. and Stone, C. (1984), *Classification and Regression Trees*, Wadsworth.
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@@ -194,5 +194,3 @@ The sample below (currently using the obsolete ``CvMat`` structures) demonstrate
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cvReleaseMat( &trainData );
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return 0;
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}
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@@ -278,4 +278,3 @@ Returns neurons weights of the particular layer.
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.. ocv:function:: double* CvANN_MLP::get_weights(int layer)
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:param layer: Index of the particular layer.
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@@ -161,4 +161,3 @@ Predicts the response for a sample.
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The method is used to predict the response for a new sample. In case of a classification, the method returns the class label. In case of a regression, the method returns the output function value. The input sample must have as many components as the ``train_data`` passed to ``train`` contains. If the ``var_idx`` parameter is passed to ``train``, it is remembered and then is used to extract only the necessary components from the input sample in the method ``predict``.
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The suffix ``const`` means that prediction does not affect the internal model state, so the method can be safely called from within different threads.
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