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  2. Logistic function - Wikipedia

    en.wikipedia.org/wiki/Logistic_function

    Logistic function. A logistic function or logistic curve is a common S-shaped curve ( sigmoid curve) with the equation. where. is the carrying capacity, the supremum of the values of the function; is the logistic growth rate, the steepness of the curve; and. is the value of the function's midpoint. [1]

  3. Logistic distribution - Wikipedia

    en.wikipedia.org/wiki/Logistic_distribution

    In probability theory and statistics, the logistic distribution is a continuous probability distribution. Its cumulative distribution function is the logistic function, which appears in logistic regression and feedforward neural networks. It resembles the normal distribution in shape but has heavier tails (higher kurtosis ).

  4. Logistic map - Wikipedia

    en.wikipedia.org/wiki/Logistic_map

    Logistic map. The logistic map is a polynomial mapping (equivalently, recurrence relation) of degree 2, often referred to as an archetypal example of how complex, chaotic behaviour can arise from very simple nonlinear dynamical equations.

  5. Sigmoid function - Wikipedia

    en.wikipedia.org/wiki/Sigmoid_function

    A sigmoid function is any mathematical function whose graph has a characteristic S-shaped or sigmoid curve . A common example of a sigmoid function is the logistic function shown in the first figure and defined by the formula: [1] Other standard sigmoid functions are given in the Examples section. In some fields, most notably in the context of ...

  6. Logistic regression - Wikipedia

    en.wikipedia.org/wiki/Logistic_regression

    An explanation of logistic regression can begin with an explanation of the standard logistic function. The logistic function is a sigmoid function, which takes any real input , and outputs a value between zero and one. [2] For the logit, this is interpreted as taking input log-odds and having output probability.

  7. Loss functions for classification - Wikipedia

    en.wikipedia.org/wiki/Loss_functions_for...

    e. Bayes consistent loss functions: Zero-one loss (gray), Savage loss (green), Logistic loss (orange), Exponential loss (purple), Tangent loss (brown), Square loss (blue) In machine learning and mathematical optimization, loss functions for classification are computationally feasible loss functions representing the price paid for inaccuracy of ...

  8. Generalised logistic function - Wikipedia

    en.wikipedia.org/wiki/Generalised_logistic_function

    The generalized logistic function or curve is an extension of the logistic or sigmoid functions. Originally developed for growth modelling, it allows for more flexible S-shaped curves. The function is sometimes named Richards's curve after F. J. Richards, who proposed the general form for the family of models in 1959.

  9. Log-logistic distribution - Wikipedia

    en.wikipedia.org/wiki/Log-logistic_distribution

    In probability and statistics, the log-logistic distribution (known as the Fisk distribution in economics) is a continuous probability distribution for a non-negative random variable. It is used in survival analysis as a parametric model for events whose rate increases initially and decreases later, as, for example, mortality rate from cancer ...