Machine Learning - Machine Learning, Knowledge Discovery in Databases (KDD) and Data Mining

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 is impersonal, it takes the pride away from a piece of work, the individual merits and defects that go along with all work that is not done by a machine—which is to say, its little bit of humanity.
    Friedrich Nietzsche (1844–1900)

    A young man is not a proper hearer of lectures on political science; for he is inexperienced in the actions that occur in life, but its discussions start from these and are about these; and, further, since he tends to follow his passions, his study will be vain and unprofitable, because the end that is aimed at is not knowledge but action. And it makes no difference whether he is young in years or youthful in character.
    Aristotle (384–323 B.C.)

    We are all humiliated by the sudden discovery of a fact which has existed very comfortably and perhaps been staring at us in private while we have been making up our world entirely without it.
    George Eliot [Mary Ann (or Marian)

    To write it, it took three months; to conceive it three minutes; to collect the data in it—all my life.
    F. Scott Fitzgerald (1896–1940)

    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)