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 verb "ground truthing" refers to the process of gathering the proper objective data for this test. Compare with Gold standard (test).
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 that ground truth will correlate to inaccuracies in the resulting spam/non-spam verdicts.
Read more about this topic: Ground Truth
Famous quotes containing the words statistics, machine and/or learning:
“July 4. Statistics show that we lose more fools on this day than in all the other days of the year put together. This proves, by the number left in stock, that one Fourth of July per year is now inadequate, the country has grown so.”
—Mark Twain [Samuel Langhorne Clemens] (1835–1910)
“Goodbye, boys; I’m under arrest. I may have to go to jail. I may not see you for a long time. Keep up the fight! Don’t surrender! Pay no attention to the injunction machine at Parkersburg. The Federal judge is a scab anyhow. While you starve he plays golf. While you serve humanity, he serves injunctions for the money powers.”
—Mother Jones (1830–1930)
“This great purple butterfly,
In the prison of my hands,
Has a learning in his eye
Not a poor fool understands.
Once he lived a schoolmaster
With a stark, denying look....”
—William Butler Yeats (1865–1939)