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  2. Learning log - Wikipedia

    en.wikipedia.org/wiki/Learning_log

    Learning log. Two students share and compare their learning logs. Learning Logs are a personalized learning resource for children. In the learning logs, the children record their responses to learning challenges set by their teachers. Each log is a unique record of the child's thinking and learning. The logs are usually a visually oriented ...

  3. Logarithm - Wikipedia

    en.wikipedia.org/wiki/Logarithm

    In mathematics, the logarithm is the inverse function to exponentiation. That means that the logarithm of a number x to the base b is the exponent to which b must be raised to produce x. For example, since 1000 = 103, the logarithm base of 1000 is 3, or log10 (1000) = 3.

  4. Likelihood function - Wikipedia

    en.wikipedia.org/wiki/Likelihood_function

    The χ 2 distribution given by Wilks' theorem converts the region's log-likelihood differences into the "confidence" that the population's "true" parameter set lies inside. The art of choosing the fixed log-likelihood difference is to make the confidence acceptably high while keeping the region acceptably small (narrow range of estimates).

  5. Maximum likelihood estimation - Wikipedia

    en.wikipedia.org/wiki/Maximum_likelihood_estimation

    In statistics, maximum likelihood estimation ( MLE) is a method of estimating the parameters of an assumed probability distribution, given some observed data. This is achieved by maximizing a likelihood function so that, under the assumed statistical model, the observed data is most probable. The point in the parameter space that maximizes the ...

  6. Log–log plot - Wikipedia

    en.wikipedia.org/wiki/Loglog_plot

    Comparison of Linear, Concave, and Convex Functions In original (left) and log10 (right) scales. In science and engineering, a loglog graph or loglog plot is a two-dimensional graph of numerical data that uses logarithmic scales on both the horizontal and vertical axes. Power functions – relationships of the form – appear as straight ...

  7. Probably approximately correct learning - Wikipedia

    en.wikipedia.org/wiki/Probably_approximately...

    In computational learning theory, probably approximately correct ( PAC) learning is a framework for mathematical analysis of machine learning. It was proposed in 1984 by Leslie Valiant. [ 1] In this framework, the learner receives samples and must select a generalization function (called the hypothesis) from a certain class of possible functions.

  8. Log-normal distribution - Wikipedia

    en.wikipedia.org/wiki/Log-normal_distribution

    In probability theory, a log-normal (or lognormal) distribution is a continuous probability distribution of a random variable whose logarithm is normally distributed. Thus, if the random variable X is log-normally distributed, then Y = ln (X) has a normal distribution. [ 2][ 3] Equivalently, if Y has a normal distribution, then the exponential ...

  9. Expectation–maximization algorithm - Wikipedia

    en.wikipedia.org/wiki/Expectation–maximization...

    t. e. In statistics, an expectation–maximization ( EM) algorithm is an iterative method to find (local) maximum likelihood or maximum a posteriori (MAP) estimates of parameters in statistical models, where the model depends on unobserved latent variables. [ 1] The EM iteration alternates between performing an expectation (E) step, which ...