In the context of machine learning, there are three main approaches and techniques: supervised, unsupervised, and semi-supervised machine learning.
Supervised learning problems can be further grouped into regression and classification problems. A classification problem happens when the output variable is a category, and a regression problem is when the output variable is a real value. For example, if we predict the possibility of rain in some regions and assign two labels (rain/no rain), this is a classification problem. On the other hand, if the output of our model is the probability associated with the rain, this is a regression problem.
OpenCV provides the cv2.kmeans() function, implementing a k-means clustering algorithm, ...
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