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  2. Entropy in thermodynamics and information theory - Wikipedia

    en.wikipedia.org/wiki/Entropy_in_thermodynamics...

    The defining expression for entropy in the theory of information established by Claude E. Shannon in 1948 is of the form: where is the probability of the message taken from the message space M, and b is the base of the logarithm used. Common values of b are 2, Euler's number e, and 10, and the unit of entropy is shannon (or bit) for b = 2, nat ...

  3. Information gain (decision tree) - Wikipedia

    en.wikipedia.org/wiki/Information_gain_(decision...

    Thus, by definition from equation (i): (Information gain) = H(t) - H(s,t) After all the steps, gain(s), where s is a candidate split for the example is: gain(s) = 0.985 – 0.857 = 0.128 The newly created tree with the root node split based on Mutation 3. Mutation 3 had the highest information gain, so it was selected as the split.

  4. Entropy (information theory) - Wikipedia

    en.wikipedia.org/wiki/Entropy_(information_theory)

    In information theory, the entropy of a random variable quantifies the average level of uncertainty or information associated with the variable's potential states or possible outcomes. This measures the expected amount of information needed to describe the state of the variable, considering the distribution of probabilities across all potential ...

  5. Differential entropy - Wikipedia

    en.wikipedia.org/wiki/Differential_entropy

    Differential entropy (also referred to as continuous entropy) is a concept in information theory that began as an attempt by Claude Shannon to extend the idea of (Shannon) entropy (a measure of average surprisal) of a random variable, to continuous probability distributions. Unfortunately, Shannon did not derive this formula, and rather just ...

  6. Conditional entropy - Wikipedia

    en.wikipedia.org/wiki/Conditional_entropy

    The violet is the mutual information . In information theory, the conditional entropy quantifies the amount of information needed to describe the outcome of a random variable given that the value of another random variable is known. Here, information is measured in shannons, nats, or hartleys. The entropy of conditioned on is written as .

  7. Entropy (order and disorder) - Wikipedia

    en.wikipedia.org/wiki/Entropy_(order_and_disorder)

    A measure of disorder in the universe or of the unavailability of the energy in a system to do work. [7] Entropy and disorder also have associations with equilibrium. [8] Technically, entropy, from this perspective, is defined as a thermodynamic property which serves as a measure of how close a system is to equilibrium—that is, to perfect ...

  8. Entropy as an arrow of time - Wikipedia

    en.wikipedia.org/wiki/Entropy_as_an_arrow_of_time

    Entropy is one of the few quantities in the physical sciences that require a particular direction for time, sometimes called an arrow of time. As one goes "forward" in time, the second law of thermodynamics says, the entropy of an isolated system can increase, but not decrease. Thus, entropy measurement is a way of distinguishing the past from ...

  9. Entropy (statistical thermodynamics) - Wikipedia

    en.wikipedia.org/wiki/Entropy_(statistical...

    Entropy (statistical thermodynamics) The concept entropy was first developed by German physicist Rudolf Clausius in the mid-nineteenth century as a thermodynamic property that predicts that certain spontaneous processes are irreversible or impossible. In statistical mechanics, entropy is formulated as a statistical property using probability ...