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  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. Feature selection - Wikipedia

    en.wikipedia.org/wiki/Feature_selection

    One other popular approach is the Recursive Feature Elimination algorithm, [15] commonly used with Support Vector Machines to repeatedly construct a model and remove features with low weights. Embedded methods are a catch-all group of techniques which perform feature selection as part of the model construction process.

  4. Log-linear analysis - Wikipedia

    en.wikipedia.org/wiki/Log-linear_analysis

    Backward elimination is used to determine which of the model components are necessary to retain in order to best account for the data. Log-linear analysis starts with the saturated model and the highest order interactions are removed until the model no longer accurately fits the data.

  5. Euler method - Wikipedia

    en.wikipedia.org/wiki/Euler_method

    The backward Euler method is an implicit method, meaning that the formula for the backward Euler method has + on both sides, so when applying the backward Euler method we have to solve an equation. This makes the implementation more costly.

  6. Forward–backward algorithm - Wikipedia

    en.wikipedia.org/wiki/Forward–backward_algorithm

    The first pass goes forward in time while the second goes backward in time; hence the name forward–backward algorithm. The term forward–backward algorithm is also used to refer to any algorithm belonging to the general class of algorithms that operate on sequence models in a forward–backward manner. In this sense, the descriptions in the ...

  7. Backward induction - Wikipedia

    en.wikipedia.org/wiki/Backward_induction

    Limited backward induction is a deviation from fully rational backward induction. It involves enacting the regular process of backward induction without perfect foresight. Theoretically, this occurs when one or more players have limited foresight and cannot perform backward induction through all terminal nodes. [ 15 ]

  8. Backward chaining - Wikipedia

    en.wikipedia.org/wiki/Backward_chaining

    Backward chaining is implemented in logic programming by SLD resolution. Both rules are based on the modus ponens inference rule. It is one of the two most commonly used methods of reasoning with inference rules and logical implications – the other is forward chaining. Backward chaining systems usually employ a depth-first search strategy, e ...

  9. Tridiagonal matrix algorithm - Wikipedia

    en.wikipedia.org/wiki/Tridiagonal_matrix_algorithm

    Simplified forms of Gaussian elimination have been developed for these situations. [ 6 ] The textbook Numerical Mathematics by Alfio Quarteroni , Sacco and Saleri, lists a modified version of the algorithm which avoids some of the divisions (using instead multiplications), which is beneficial on some computer architectures.