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:
“I brush my hair,
waiting in the pain machine for my bones to get hard,
for the soft, soft bones that were laid apart
and were screwed together. They will knit.
And the other corpse, the fractured heart,
I feed it piecemeal, little chalice. I’m good to it.”
—Anne Sexton (1928–1974)
“But a mother is like a broomstick or like the sun in the heavens, it does not matter which as far as one’s knowledge of her is concerned: the broomstick is there and the sun is there; and whether the child is beaten by it or warmed and enlightened by it, it accepts it as a fact in nature, and does not conceive it as having had youth, passions, and weaknesses, or as still growing, yearning, suffering, and learning.”
—George Bernard Shaw (1856–1950)
“The discovery of Pennsylvania’s coal and iron was the deathblow to Allaire. The works were moved to Pennsylvania so hurriedly that for years pianos and the larger pieces of furniture stood in the deserted houses.”
—For the State of New Jersey, U.S. public relief program (1935-1943)
“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)
“It’s a mining town in lotus land.”
—F. Scott Fitzgerald (1896–1940)