Submitter Variables Constraints Density Status Group Objective MPS File
Berk Ustun 715 723 1.6023e-02 open ustun 35.7139210526316 breastcancer-regularized.mps.gz

MIP to create optimized data-driven scoring systems. See: https://github.com/ustunb/miplib2017-slim#miplib2017-slim for a description.

Instance Statistics

Detailed explanation of the following tables can be found here.

Size Related Properties
Original Presolved
Variables 715 715
Constraints 723 723
Binaries 692 692
Integers 14 14
Continuous 9 9
Implicit Integers 0 0
Fixed Variables 0 0
Nonzero Density 0.016023 0.016023
Nonzeroes 8283 8283
Constraint Classification Properties
Original Presolved
Total 723 723
Empty 0 0
Free 0 0
Singleton 0 0
Aggregations 0 0
Precedence 0 0
Variable Bound 36 36
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 0 0
General Linear 687 687
Indicator 0 0

Structure

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

value min median mean max
Components 1.041393
Constraint % 0.276625 0.525588 0.55325 0.55325
Variable % 0.419580 3.762240 0.41958 33.84620
Score 0.051414

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 35.71392 9.3e-06 0 0 - 2018-10-11 Solution found during MIPLIB2017 problem selection.

Similar instances in collection

The following instances are most similar to breastcancer-regularized 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
adult-regularized 32674 32597 41 36 32709 417567 Berk Ustun ustun open 7022.953543478*
mushroom-best 8468 8237 118 113 8580 188735 Berk Ustun ustun easy 0.0553337612
adult-max5features 32674 32597 41 36 32709 417567 Berk Ustun ustun open 5848.097508813*
lectsched-4-obj 7901 7665 236 0 14163 82428 Harald Schilly lectsched easy 4
lectsched-5-obj 21805 21389 416 0 38884 239608 Harald Schilly lectsched easy 24

Reference

@article{
    ustun2015slim,
    year = {2015},
    issn = {0885-6125},
    journal = {Machine Learning},
    doi = {10.1007/s10994-015-5528-6},
    title = {Supersparse linear integer models for optimized medical scoring systems},
    url = {http://dx.doi.org/10.1007/s10994-015-5528-6},
    publisher = { Springer US},
    author = {Ustun, Berk and Rudin, Cynthia},
    pages = {1-43},
    language = {English}
}

Last Update Nov 17, 2018 by Gregor Hendel
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