adult-max5features

variable_bound general_linear

Submitter Variables Constraints Density Status Group Objective MPS File
Berk Ustun 32674 32709 3.90712e-04 open ustun 5848.097508813* adult-max5features.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 32674 32674
Constraints 32709 32709
Binaries 32597 32597
Integers 41 41
Continuous 36 36
Implicit Integers 0 0
Fixed Variables 0 0
Nonzero Density 0.000390712 0.000390712
Nonzeroes 417567 417567
Constraint Classification Properties
Original Presolved
Total 32709 32709
Empty 0 0
Free 0 0
Singleton 0 0
Aggregations 0 0
Precedence 0 0
Variable Bound 144 144
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 32565 32565
Indicator 0 0

Structure

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

value min median mean max
Components 1.568202
Constraint % 0.0122291 0.0122291 0.0122291 0.0122291
Variable % 0.0091800 0.0091800 0.0091800 0.0091800
Score 0.004402

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 5848.098 5848.098 0 0 0 - 2018-10-11 Solution found during MIPLIB2017 problem selection.

Similar instances in collection

The following instances are most similar to adult-max5features 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 Status Variables Binaries Integers Continuous Constraints Nonz. Submitter Group Objective Tags
mushroom-best easy 8468 8237 118 113 8580 188735 Berk Ustun ustun 0.0553337612 benchmark benchmark_suitable variable_bound general_linear
adult-regularized open 32674 32597 41 36 32709 417567 Berk Ustun ustun 7022.953543478* variable_bound general_linear
breastcancer-regularized open 715 692 14 9 723 8283 Berk Ustun ustun 35.7139210526316* numerics variable_bound general_linear
neos-1456979 easy 4605 4245 180 180 6770 36440 NEOS Server Submission neos-pseudoapplication-102 176 benchmark decomposition benchmark_suitable variable_bound set_partitioning set_packing cardinality knapsack mixed_binary general_linear
neos-686190 easy 3660 3600 60 0 3664 18085 NEOS Server Submission neos-pseudoapplication-60 6730 benchmark_suitable precedence variable_bound set_partitioning set_covering general_linear

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 Apr 09, 2019 by Gregor Hendel
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