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  2. Logistic regression - Wikipedia

    en.wikipedia.org/wiki/Logistic_regression

    Logistic regression is used in various fields, including machine learning, most medical fields, and social sciences. For example, the Trauma and Injury Severity Score (), which is widely used to predict mortality in injured patients, was originally developed by Boyd et al. using logistic regression. [6]

  3. Discriminative model - Wikipedia

    en.wikipedia.org/wiki/Discriminative_model

    Types of discriminative models include logistic regression (LR), conditional random fields (CRFs), decision trees among many others. Generative model approaches which uses a joint probability distribution instead, include naive Bayes classifiers, Gaussian mixture models, variational autoencoders, generative adversarial networks and others.

  4. Multinomial logistic regression - Wikipedia

    en.wikipedia.org/.../Multinomial_logistic_regression

    Multinomial logistic regression is known by a variety of other names, including polytomous LR, [2] [3] multiclass LR, softmax regression, multinomial logit (mlogit), the maximum entropy (MaxEnt) classifier, and the conditional maximum entropy model.

  5. Regression analysis - Wikipedia

    en.wikipedia.org/wiki/Regression_analysis

    For example, a researcher is building a linear regression model using a dataset that contains 1000 patients (). If the researcher decides that five observations are needed to precisely define a straight line ( m {\displaystyle m} ), then the maximum number of independent variables ( n {\displaystyle n} ) the model can support is 4, because

  6. Conditional logistic regression - Wikipedia

    en.wikipedia.org/.../Conditional_logistic_regression

    Conditional logistic regression is an extension of logistic regression that allows one to account for stratification and matching. Its main field of application is observational studies and in particular epidemiology. It was devised in 1978 by Norman Breslow, Nicholas Day, Katherine Halvorsen, Ross L. Prentice and C. Sabai. [1]

  7. One in ten rule - Wikipedia

    en.wikipedia.org/wiki/One_in_ten_rule

    In statistics, the one in ten rule is a rule of thumb for how many predictor parameters can be estimated from data when doing regression analysis (in particular proportional hazards models in survival analysis and logistic regression) while keeping the risk of overfitting and finding spurious correlations low. The rule states that one ...

  8. Logistic function - Wikipedia

    en.wikipedia.org/wiki/Logistic_function

    The standard logistic function is the logistic function with parameters =, =, =, which yields = + = + = / / + /.In practice, due to the nature of the exponential function, it is often sufficient to compute the standard logistic function for over a small range of real numbers, such as a range contained in [−6, +6], as it quickly converges very close to its saturation values of 0 and 1.

  9. Logistic map - Wikipedia

    en.wikipedia.org/wiki/Logistic_map

    An example of a spider web projection of a trajectory on the graph of the logistic map, and the locations of the fixed points and on the graph. Graphs of maps, especially those of one variable such as the logistic map, are key to understanding the behavior of the map.