enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Stepwise regression - Wikipedia

    en.wikipedia.org/wiki/Stepwise_regression

    The main approaches for stepwise regression are: Forward selection, which involves starting with no variables in the model, testing the addition of each variable using a chosen model fit criterion, adding the variable (if any) whose inclusion gives the most statistically significant improvement of the fit, and repeating this process until none improves the model to a statistically significant ...

  3. Decision tree learning - Wikipedia

    en.wikipedia.org/wiki/Decision_tree_learning

    Regression tree analysis is when the predicted outcome can be considered a real number (e.g. the price of a house, or a patient's length of stay in a hospital). The term classification and regression tree (CART) analysis is an umbrella term used to refer to either of the above procedures, first introduced by Breiman et al. in 1984. [ 7 ]

  4. Minimum description length - Wikipedia

    en.wikipedia.org/wiki/Minimum_description_length

    MDL applies in machine learning when algorithms (machines) generate descriptions. Learning occurs when an algorithm generates a shorter description of the same data set. The theoretic minimum description length of a data set, called its Kolmogorov complexity, cannot, however, be computed.

  5. Statistical learning theory - Wikipedia

    en.wikipedia.org/wiki/Statistical_learning_theory

    Statistical learning theory is a framework for machine learning drawing from the fields of statistics and functional analysis. [ 1 ] [ 2 ] [ 3 ] Statistical learning theory deals with the statistical inference problem of finding a predictive function based on data.

  6. Regression analysis - Wikipedia

    en.wikipedia.org/wiki/Regression_analysis

    In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships between a dependent variable (often called the outcome or response variable, or a label in machine learning parlance) and one or more error-free independent variables (often called regressors, predictors, covariates, explanatory ...

  7. Ensemble learning - Wikipedia

    en.wikipedia.org/wiki/Ensemble_learning

    Ensemble learning, including both regression and classification tasks, can be explained using a geometric framework. [15] Within this framework, the output of each individual classifier or regressor for the entire dataset can be viewed as a point in a multi-dimensional space.

  8. C4.5 algorithm - Wikipedia

    en.wikipedia.org/wiki/C4.5_algorithm

    C4.5 is an algorithm used to generate a decision tree developed by Ross Quinlan. [1] C4.5 is an extension of Quinlan's earlier ID3 algorithm.The decision trees generated by C4.5 can be used for classification, and for this reason, C4.5 is often referred to as a statistical classifier.

  9. Linear regression - Wikipedia

    en.wikipedia.org/wiki/Linear_regression

    Linear regression plays an important role in the subfield of artificial intelligence known as machine learning. The linear regression algorithm is one of the fundamental supervised machine-learning algorithms due to its relative simplicity and well-known properties.