breeze.optimize.linear
Type members
Classlikes
Simple LP solver based on http://en.wikipedia.org/wiki/Karmarkar's_algorithm Note that this is not Karmarkar's algorithm.
Simple LP solver based on http://en.wikipedia.org/wiki/Karmarkar's_algorithm Note that this is not Karmarkar's algorithm.
- Companion:
- object
Algorithms for finding a bipartite matching. We include one optimal algorithm (KuhnMunkres) and one greedy algorithm (competitive linking).
Algorithms for finding a bipartite matching. We include one optimal algorithm (KuhnMunkres) and one greedy algorithm (competitive linking).
Algorithms find minimum matchings.
mixed 0-1 ILP Solver based on Branch and bound
mixed 0-1 ILP Solver based on Branch and bound
- See also:
Solve argmin (a dot x + .5 * x dot (B * x) + .5 * normSquaredPenalty * (x dot x)) for x subject to norm(x) <= maxNormValue
Solve argmin (a dot x + .5 * x dot (B * x) + .5 * normSquaredPenalty * (x dot x)) for x subject to norm(x) <= maxNormValue
Based on the code from "Trust Region Newton Method for Large-Scale Logistic Regression"
- @author dlwh
Algorithm to find a minimum cost matching on a bipartite graph.
Algorithm to find a minimum cost matching on a bipartite graph.
Implements the hungarian algorithm.
DSL for LinearPrograms. Not thread-safe per instance. Make multiple instances
DSL for LinearPrograms. Not thread-safe per instance. Make multiple instances
Basic example:
val lp = new LP
import lp._
val x = new Positive("x")
val y = new Positive("y")
val result = maximize ( (3 * x+ 4 * y)
subjectTo( x <= 3, y <= 1))
result.valueOf(x) // 3
- Companion:
- object
NNLS solves nonnegative least squares problems using a modified projected gradient method.
NNLS solves nonnegative least squares problems using a modified projected gradient method.
- Value parameters:
- maxIters
user defined maximum iterations
- Companion:
- object
Power Method to compute maximum eigen value and companion object to compute minimum eigen value through inverse power iterations
Power Method to compute maximum eigen value and companion object to compute minimum eigen value through inverse power iterations
- Companion:
- object