In information theory, the conditional entropy quantifies the amount of information needed to describe the outcome of a random variable Y {\displaystyle...
11 KB (2,142 words) - 05:02, 6 July 2025
The conditional quantum entropy is an entropy measure used in quantum information theory. It is a generalization of the conditional entropy of classical...
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In information theory, the entropy of a random variable quantifies the average level of uncertainty or information associated with the variable's potential...
71 KB (10,208 words) - 07:29, 15 July 2025
Despite similar notation, joint entropy should not be confused with cross-entropy. The conditional entropy or conditional uncertainty of X given random...
69 KB (8,508 words) - 04:47, 12 July 2025
Shannon entropy and its quantum generalization, the von Neumann entropy, one can define a conditional version of min-entropy. The conditional quantum...
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In information theory, the cross-entropy between two probability distributions p {\displaystyle p} and q {\displaystyle q} , over the same underlying...
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Kullback–Leibler divergence (redirect from Kullback–Leibler entropy)
statistics, the Kullback–Leibler (KL) divergence (also called relative entropy and I-divergence), denoted D KL ( P ∥ Q ) {\displaystyle D_{\text{KL}}(P\parallel...
77 KB (13,075 words) - 21:27, 5 July 2025
Mutual information (redirect from Mutual entropy)
{\displaystyle (x,y)} . Expressed in terms of the entropy H ( ⋅ ) {\displaystyle H(\cdot )} and the conditional entropy H ( ⋅ | ⋅ ) {\displaystyle H(\cdot |\cdot...
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the joint entropy. This is equivalent to the fact that the conditional quantum entropy may be negative, while the classical conditional entropy may never...
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{H} (X_{1})+\ldots +\mathrm {H} (X_{n})} Joint entropy is used in the definition of conditional entropy: 22 H ( X | Y ) = H ( X , Y ) − H ( Y ) {\displaystyle...
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for example, differential entropy may be negative. The differential analogies of entropy, joint entropy, conditional entropy, and mutual information are...
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( Y ∣ X ) {\displaystyle H(Y\mid X)} are the entropy of the output signal Y and the conditional entropy of the output signal given the input signal, respectively:...
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to a stochastic process. For a strongly stationary process, the conditional entropy for latest random variable eventually tend towards this rate value...
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of Secrecy Systems conditional entropy conditional quantum entropy confusion and diffusion cross-entropy data compression entropic uncertainty (Hirchman...
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Logistic regression (redirect from Conditional logit analysis)
X)\end{aligned}}} where H ( Y ∣ X ) {\displaystyle H(Y\mid X)} is the conditional entropy and D KL {\displaystyle D_{\text{KL}}} is the Kullback–Leibler divergence...
121 KB (19,414 words) - 03:19, 24 July 2025
joint, conditional differential entropy, and relative entropy are defined in a similar fashion. Unlike the discrete analog, the differential entropy has...
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y,z)dxdydz} . Alternatively, we may write in terms of joint and conditional entropies as I ( X ; Y | Z ) = H ( X , Z ) + H ( Y , Z ) − H ( X , Y , Z )...
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identically-distributed random variable, and the operational meaning of the Shannon entropy. Named after Claude Shannon, the source coding theorem shows that, in the...
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In physics, the von Neumann entropy, named after John von Neumann, is a measure of the statistical uncertainty within a description of a quantum system...
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variable e in terms of its entropy. One can then subtract the content of e that is irrelevant to h (given by its conditional entropy conditioned on h) from...
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In statistics, a maximum-entropy Markov model (MEMM), or conditional Markov model (CMM), is a graphical model for sequence labeling that combines features...
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Rényi entropy is a quantity that generalizes various notions of entropy, including Hartley entropy, Shannon entropy, collision entropy, and min-entropy. The...
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Neumann entropy, S(ρ) the joint quantum entropy and S(ρA|ρB) a quantum generalization of conditional entropy (not to be confused with conditional quantum...
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script, and noting that the Indus script appears to have a similar conditional entropy to Old Tamil. These scholars have proposed readings of many signs;...
65 KB (6,446 words) - 01:29, 5 June 2025
quantum relative entropy is a measure of distinguishability between two quantum states. It is the quantum mechanical analog of relative entropy. For simplicity...
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H(X\mid Y)=-\sum _{i,j}P(x_{i},y_{j})\log P(x_{i}\mid y_{j})} is the conditional entropy, P ( e ) = P ( X ≠ X ~ ) {\displaystyle P(e)=P(X\neq {\tilde {X}})}...
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Information theory Entropy Differential entropy Conditional entropy Joint entropy Mutual information Directed information Conditional mutual information...
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Multinomial logistic regression (redirect from Maximum entropy classifier)
regression, multinomial logit (mlogit), the maximum entropy (MaxEnt) classifier, and the conditional maximum entropy model. Multinomial logistic regression is used...
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that tf–idf employs." The conditional entropy of a "randomly chosen" document in the corpus D {\displaystyle D} , conditional to the fact it contains a...
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Information diagram (redirect from Entropy diagram)
relationships among Shannon's basic measures of information: entropy, joint entropy, conditional entropy and mutual information. Information diagrams are a useful...
3 KB (494 words) - 06:20, 4 March 2024