|PDF Title :||Learning OpenCV 3|
|Total Page :||1018 Pages|
|PDF Size :||8.0 MB|
|PDF Link :||Available|
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Learning OpenCV 3 – Book
Many models in the ML library may be trained on a selected feature subset and/or on a selected sample subset of the training set. To make this easier for the user, the cv::ml::TrainData::create() method includes the vectors varIdx and sampleIdx as parameters. The varIdx vector can be used to identify specific variables (features) of interest, while sampleIdx can identify specific data points of interest.
Either of these may simply be omitted or set to cv::noArray() (the default value) to indicate that you would like to use “all of the features” or “all of the points.” Both vectors are either provided as lists of zero-based indices or as masks of active variables/samples, where a nonzero value signifies active. In the former case, the vector must be of type CV_32SC1 and may have any length.
Learning OpenCV 3 PDF
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