This Google Earth Engine video tutorial will show you how to do Accuracy Assessment from Supervised Classification using the Sentinel2 image and Random Forest Algorithm.

Supervised learning is the machine learning task of learning a function that maps an input to an output based on example inputoutput pairs. It infers a function from labeled training data consisting of a set of training examples (Wikipedia).

Random forests or random decision forests are an ensemble learning method for classification, regression, and other tasks that operate by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes (classification) or mean prediction (regression) of the individual trees. Random decision forests correct for decision trees' habit of overfitting to their training set (Wikipedia).

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