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#Com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.steepestdescent Classes and Interfaces - 6 results found.
| Name | Description | Type | Package | Framework |
| FirstOrderMinimizer | This implements the steepest descent line search using the first order expansion of the Taylor's series. | Class | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.steepestdescent | SuanShu |
| FirstOrderMinimizer .Method | the available methods to do line searchThe line search is done analytically. | Class | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.steepestdescent | SuanShu |
| GaussNewtonMinimizer | The Gauss-Newton method is a steepest descent method to minimize a real vector function in the form: f(x) = [f_1(x), f_2(x), . | Class | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.steepestdescent | SuanShu |
| GaussNewtonMinimizer .MySteepestDescent | Class | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.steepestdescent | SuanShu | |
| NewtonRaphsonMinimizer | The Newton-Raphson method is a second order steepest descent method that is based on the quadratic approximation of the Taylor series. | Class | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.steepestdescent | SuanShu |
| SteepestDescentMinimizer | A steepest descent algorithm finds the minimum by moving along the negative of the steepest gradient direction. | Class | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.steepestdescent | SuanShu |