Submitter Variables Constraints Density Status Group Objective MPS File
Toni Sorrell 241 180 9.26694e-02 easy supportvectormachine 0.33652753 gsvm2rl3.mps.gz

Suport vector machine with ramp loss. GSVM2-RL is the formulation found in Hess E. and Brooks P. (2015) paper, The Support Vector Machine and Mixed Integer Linear Programming: Ramp Loss SVM with L1-Norm Regularization

Instance Statistics

Detailed explanation of the following tables can be found here.

Size Related Properties
Original Presolved
Variables 241 241
Constraints 180 180
Binaries 60 60
Integers 0 0
Continuous 181 181
Implicit Integers 0 0
Fixed Variables 0 0
Nonzero Density 0.0926694 0.0926694
Nonzeroes 4020 4020
Constraint Classification Properties
Original Presolved
Total 180 180
Empty 0 0
Free 0 0
Singleton 0 0
Aggregations 0 0
Precedence 60 60
Variable Bound 60 60
Set Partitioning 0 0
Set Packing 0 0
Set Covering 0 0
Cardinality 0 0
Invariant Knapsack 0 0
Equation Knapsack 0 0
Bin Packing 0 0
Knapsack 0 0
Integer Knapsack 0 0
Mixed Binary 60 60
General Linear 0 0
Indicator 0 0

Structure

Available nonzero structure and decomposition information. Further information can be found here.

value min median mean max
Components 1.785330
Constraint % 1.111110 1.111110 1.111110 1.111110
Variable % 0.829876 0.829876 0.829876 0.829876
Score 0.661134

Best Known Solution(s)

Find solutions below. Download the archive containing all solutions from the Download page.

ID Objective Exact Int. Viol Cons. Viol Obj. Viol Submitter Date Description
1 0.3365275 0.3365275 0 0 0 - 2018-10-13 Solution found during MIPLIB2017 problem selection.

Similar instances in collection

The following instances are most similar to gsvm2rl3 in the collection. This similarity analysis is based on 100 scaled instance features describing properties of the variables, objective function, bounds, constraints, and right hand sides.

Instance Variables Binaries Integers Continuous Constraints Nonz. Submitter Group Status Objective
gsvm2rl5 401 100 0 301 300 10700 Toni Sorrell supportvectormachine open 5.4230535252*
gsvm2rl9 801 200 0 601 600 41400 Toni Sorrell supportvectormachine open 7438.181167768*
gsvm2rl12 2001 500 0 1501 1500 253500 Toni Sorrell supportvectormachine open 22.12011638092*
gsvm2rl11 2001 500 0 1501 1500 253500 Toni Sorrell supportvectormachine open 18121.63800478*
neos-619167 3452 400 0 3052 6800 20020 NEOS Server Submission neos-pseudoapplication-83 easy 1.66489361858996

Reference

@article{hess2015support,
  title={The Support Vector Machine and Mixed Integer Linear Programming: Ramp Loss SVM with L1-Norm Regularization},
  author={Hess, Eric J and Brooks, J Paul},
  year={2015}
}

Last Update Nov 19, 2018 by Gregor Hendel
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