Lecture 5 : January 27
نویسنده
چکیده
j=1 p̂j log2(p̂j) • LP Estimator The LP Estimator works by transforming the samples {Xi}i=1 into a fingerprint, which is the vector f = (f1, f2, ...) for which fi is the number of elements in the domain that occurred i times in the sample, i.e. with empirical frequency i/n. The fingerprint is also known as the “type” of a sample. The fingerprint serves as an estimate of the histogram of the distribution which is defined as the mapping hp : (0, 1] → N ∪ {0} for which hp(x) is the number of domain elements that occur with probability exactly x. More formally, hp(x) = |{α : pα = x}|. The entropy can be computed from the histogram as follows:
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