Machine Learning, Knowledge Discovery in Databases (KDD) and Data Mining
Two terms are commonly confused, as they often employ the same methods and overlap significantly. They can be roughly defined as follows:
- Machine learning focuses on prediction, based on known properties learned from the training data.
- Data mining (which is the analysis step of Knowledge Discovery in Databases) focuses on the discovery of (previously) unknown properties on the data.
The two areas overlap in many ways: data mining uses many machine learning methods, but often with a slightly different goal in mind. On the other hand, machine learning also employs data mining methods as "unsupervised learning" or as a preprocessing step to improve learner accuracy. Much of the confusion between these two research communities (which do often have separate conferences and separate journals, ECML PKDD being a major exception) comes from the basic assumptions they work with: in machine learning, performance is usually evaluated with respect to the ability to reproduce known knowledge, while in KDD the key task is the discovery of previously unknown knowledge. Evaluated with respect to known knowledge, an uninformed (unsupervised) method will easily be outperformed by supervised methods, while in a typical KDD task, supervised methods cannot be used due to the unavailability of training data.
Read more about this topic: Machine Learning
Famous quotes containing the words machine, knowledge, discovery, data and/or mining:
“The machine has had a pernicious effect upon virtue, pity, and love, and young men used to machines which induce inertia, and fear, are near impotents.”
—Edward Dahlberg (1900–1977)
“Man is not weak; knowledge is more than equivalent to force.”
—Samuel Johnson (1709–1784)
“He is not a true man of science who does not bring some sympathy to his studies, and expect to learn something by behavior as well as by application. It is childish to rest in the discovery of mere coincidences, or of partial and extraneous laws. The study of geometry is a petty and idle exercise of the mind, if it is applied to no larger system than the starry one.”
—Henry David Thoreau (1817–1862)
“Mental health data from the 1950’s on middle-aged women showed them to be a particularly distressed group, vulnerable to depression and feelings of uselessness. This isn’t surprising. If society tells you that your main role is to be attractive to men and you are getting crow’s feet, and to be a mother to children and yours are leaving home, no wonder you are distressed.”
—Grace Baruch (20th century)
“For every nineteenth-century middle-class family that protected its wife and child within the family circle, there was an Irish or a German girl scrubbing floors in that home, a Welsh boy mining coal to keep the home-baked goodies warm, a black girl doing the family laundry, a black mother and child picking cotton to be made into clothes for the family, and a Jewish or an Italian daughter in a sweatshop making “ladies” dresses or artificial flowers for the family to purchase.”
—Stephanie Coontz (20th century)