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Ground truth
Ground truth is a term used in various fields to refer to information provided by direct observation as opposed to information provided by inference.
== Statistics and machine learning ==
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.
抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』
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