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  2. Pearson correlation coefficient - Wikipedia

    en.wikipedia.org/wiki/Pearson_correlation...

    Pearson's correlation coefficient is the covariance of the two variables divided by the product of their standard deviations. The form of the definition involves a "product moment", that is, the mean (the first moment about the origin) of the product of the mean-adjusted random variables; hence the modifier product-moment in the name.

  3. Linear programming - Wikipedia

    en.wikipedia.org/wiki/Linear_programming

    The simplex algorithm and its variants fall in the family of edge-following algorithms, so named because they solve linear programming problems by moving from vertex to vertex along edges of a polytope. This means that their theoretical performance is limited by the maximum number of edges between any two vertices on the LP polytope.

  4. Basic feasible solution - Wikipedia

    en.wikipedia.org/wiki/Basic_feasible_solution

    In the theory of linear programming, a basic feasible solution (BFS) is a solution with a minimal set of non-zero variables.Geometrically, each BFS corresponds to a vertex of the polyhedron of feasible solutions.

  5. Assignment problem - Wikipedia

    en.wikipedia.org/wiki/Assignment_problem

    One way to solve it is to invent a fourth dummy task, perhaps called "sitting still doing nothing", with a cost of 0 for the taxi assigned to it. This reduces the problem to a balanced assignment problem, which can then be solved in the usual way and still give the best solution to the problem.

  6. Dual linear program - Wikipedia

    en.wikipedia.org/wiki/Dual_linear_program

    The duality theorem states that the duality gap between the two LP problems is at least zero. Economically, it means that if the first factory is given an offer to buy its entire stock of raw material, at a per-item price of y, such that A T y ≥ c, y ≥ 0, then it should take the offer. It will make at least as much revenue as it could ...

  7. Linear programming relaxation - Wikipedia

    en.wikipedia.org/wiki/Linear_programming_relaxation

    Then, for each subproblem i, it performs the following steps. Compute the optimal solution to the linear programming relaxation of the current subproblem. That is, for each variable x j in V i , we replace the constraint that x j be 0 or 1 by the relaxed constraint that it be in the interval [0,1]; however, variables that have already been ...

  8. Independent set (graph theory) - Wikipedia

    en.wikipedia.org/wiki/Independent_set_(graph_theory)

    The independent set decision problem is NP-complete, and hence it is not believed that there is an efficient algorithm for solving it. The maximum independent set problem is NP-hard and it is also hard to approximate. Despite the close relationship between maximum cliques and maximum independent sets in arbitrary graphs, the independent set and ...

  9. Cutting-plane method - Wikipedia

    en.wikipedia.org/wiki/Cutting-plane_method

    The use of cutting planes to solve MILP was introduced by Ralph E. Gomory. Cutting plane methods for MILP work by solving a non-integer linear program, the linear relaxation of the given integer program. The theory of Linear Programming dictates that under mild assumptions (if the linear program has an optimal solution, and if the feasible ...