In Machine Learning context I have scene a lot the word Ground Truth I searched too much and found the following definition in Wikipedia:In machine learning, the term ground truth refers to the accuracy of the training set's classification for supervised learning techniques. This is used in statistical models to prove or disprove research hypotheses. The term ground truthing refers to the process of gathering the proper objective (provable) data for this test. Compare with gold standard.  Bayesian spam filtering is a common example of supervised learning. In this system, the algorithm is manually taught the differences between spam and non-spam. This depends on the ground truth of the messages used to train the algorithm  inaccuracies in the ground truth will correlate to inaccuracies in the resulting spam/non-spam verdicts.The point is that I really can not get what it means? Is that the label used for each data object or the target function which gives label to each data object or maybe something else?
What is Ground Truth
machine learning
The ground truth is what you measured for your target variable for the training and testing examples.Nearly all the time you can safely treat this the same as the label.In some cases it is not precisely the same as the label. For instance if you augment your data set, there is a subtle difference between the ground truth (your actual measurements) and how the augmented examples relate to the labels you have assigned. However, this distinction is not usually a problem.Ground truth can be wrong. It is a measurement, and there can be errors in it. In some ML scenarios it can also be a subjective measurement where it is difficult define an underlying objective truth - e.g.  expert opinion or analysis, which you are hoping to automate. Any ML model you train will be limited by the quality of the ground truth used to train and test it, and that is part of the explanation on the Wikipedia quote. It is also why published articles about ML should include full descriptions of how the data was collected.