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  2. Symbolic regression - Wikipedia

    en.wikipedia.org/wiki/Symbolic_regression

    QLattice is a quantum-inspired simulation and machine learning technology that helps search through an infinite list of potential mathematical models to solve a problem. [ 13 ] [ 14 ] Evolutionary Forest is a Genetic Programming-based automated feature construction algorithm for symbolic regression.

  3. Solution set - Wikipedia

    en.wikipedia.org/wiki/Solution_set

    In mathematics, the solution set of a system of equations or inequality is the set of all its solutions, that is the values that satisfy all equations and inequalities. [1] Also, the solution set or the truth set of a statement or a predicate is the set of all values that satisfy it. If there is no solution, the solution set is the empty set. [2]

  4. Feasible region - Wikipedia

    en.wikipedia.org/wiki/Feasible_region

    The space of all candidate solutions, before any feasible points have been excluded, is called the feasible region, feasible set, search space, or solution space. [2] This is the set of all possible solutions that satisfy the problem's constraints. Constraint satisfaction is the process of finding a point in the feasible set.

  5. Symbolic programming - Wikipedia

    en.wikipedia.org/wiki/Symbolic_programming

    In computer programming, symbolic programming is a programming paradigm in which the program can manipulate its own formulas and program components as if they were plain data.

  6. Pseudocode - Wikipedia

    en.wikipedia.org/wiki/Pseudocode

    An alternative to using mathematical pseudocode (involving set theory notation or matrix operations) for documentation of algorithms is to use a formal mathematical programming language that is a mix of non-ASCII mathematical notation and program control structures. Then the code can be parsed and interpreted by a machine.

  7. Regularization (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Regularization_(mathematics)

    These terms could be priors, penalties, or constraints. Explicit regularization is commonly employed with ill-posed optimization problems. The regularization term, or penalty, imposes a cost on the optimization function to make the optimal solution unique. Implicit regularization is all other forms of regularization. This includes, for example ...

  8. SymPy - Wikipedia

    en.wikipedia.org/wiki/SymPy

    SymPy is an open-source Python library for symbolic computation. It provides computer algebra capabilities either as a standalone application, as a library to other applications, or live on the web as SymPy Live [2] or SymPy Gamma. [3] SymPy is simple to install and to inspect because it is written entirely in Python with few dependencies.

  9. scikit-learn - Wikipedia

    en.wikipedia.org/wiki/Scikit-learn

    scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...