Concept Learning - Machine Learning Approaches To Concept Learning

Machine Learning Approaches To Concept Learning

This is a budding field due to recent progress in algorithms, computational power, and the expansion of information on the internet. Unlike the situation in Psychology, the problem of concept learning within machine learning is not one of finding the "right" theory of concept learning, but one of finding the most effective method for a given task. As such, there has been a huge proliferation of concept learning theories. In the machine learning literature, this concept learning is more typically called supervised learning or supervised classification, in contrast to unsupervised learning or unsupervised classification, in which the learner is not provided with class labels. In machine learning, algorithms of in Exemplar theory are also known as instance learners or lazy learners.

There are three important roles for machine learning.

  1. Data Mining: this is using historical data to improve decisions. An example is looking at medical records and applying it to medical knowledge when making a diagnoses.
  2. Software applications that we cannot program by hand: Examples of this are autonomous driving and speech recognition
  3. Self-customizing programs: An example of this is a newsreader that learns a readers particular interests and highlights these when the reader visits the site.

Machine learning has an exciting future. Some future advantages include; learning across full mixed-media data, learning across multiple internal databases (including the internet and news feeds), learning by active experimentation, learning decisions rather than predictions, and the possibility of programming languages with learning embedded.

Read more about this topic:  Concept Learning

Famous quotes containing the words machine, learning, approaches and/or concept:

    Psychiatric enlightenment has begun to debunk the superstition that to manage a machine you must become a machine, and that to raise masters of the machine you must mechanize the impulses of childhood.
    Erik H. Erikson (1904–1994)

    ...I didn’t consider intellectuals intelligent, I never liked them or their thoughts about life. I defined them as people who care nothing for argument, who are interested only in information; or as people who have a preference for learning things rather than experiencing them. They have opinions but no point of view.... Their talk is the gloomiest type of human discourse I know.... This is a red flag to my nature. Intellectuals, to me have no natures ...
    Margaret Anderson (1886–1973)

    As the truest society approaches always nearer to solitude, so the most excellent speech finally falls into Silence. Silence is audible to all men, at all times, and in all places. She is when we hear inwardly, sound when we hear outwardly. Creation has not displaced her, but is her visible framework and foil. All sounds are her servants, and purveyors, proclaiming not only that their mistress is, but is a rare mistress, and earnestly to be sought after.
    Henry David Thoreau (1817–1862)

    I think that Richard Nixon will go down in history as a true folk hero, who struck a vital blow to the whole diseased concept of the revered image and gave the American virtue of irreverence and skepticism back to the people.
    William Burroughs (b. 1914)