gsvm2rl5: Instance-to-Instance Comparison Results

Type: Instance
Submitter: Toni Sorrell
Description: 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
MIPLIB Entry

Parent Instance (gsvm2rl5)

All other instances below were be compared against this "query" instance.

gsvm2rl5 Raw gsvm2rl5 Decomposed gsvm2rl5 Composite of MIC top 5 gsvm2rl5 Composite of MIPLIB top 5 gsvm2rl5 Model Group Composite
Raw This is the CCM image before the decomposition procedure has been applied.
Decomposed This is the CCM image after a decomposition procedure has been applied. This is the image used by the MIC's image-based comparisons for this query instance.
Composite of MIC Top 5 Composite of the five decomposed CCM images from the MIC Top 5.
Composite of MIPLIB Top 5 Composite of the five decomposed CCM images from the MIPLIB Top 5.
Model Group Composite Image Composite of the decomposed CCM images for every instance in the same model group as this query.

MIC Top 5 Instances

These are the 5 decomposed CCM images that are most similar to decomposed CCM image for the the query instance, according to the ISS metric.

Decomposed These decomposed images were created by GCG.
gsvm2rl3 decomposed gsvm2rl9 decomposed gsvm2rl12 decomposed mik-250-20-75-5 decomposed neos-2746589-doon decomposed
Name gsvm2rl3 [MIPLIB] gsvm2rl9 [MIPLIB] gsvm2rl12 [MIPLIB] mik-250-20-75-5 [MIPLIB] neos-2746589-doon [MIPLIB]
Rank / ISS The image-based structural similarity (ISS) metric measures the Euclidean distance between the image-based feature vectors for the query instance and all other instances. A smaller ISS value indicates greater similarity.
1 / 0.422 2 / 0.466 3 / 0.505 4 / 0.554 5 / 0.934
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIC top 5.
gsvm2rl3 raw gsvm2rl9 raw gsvm2rl12 raw mik-250-20-75-5 raw neos-2746589-doon raw

MIPLIB Top 5 Instances

These are the 5 instances that are most closely related to the query instance, according to the instance statistic-based similarity measure employed by MIPLIB 2017

Decomposed These decomposed images were created by GCG.
gsvm2rl3 decomposed gsvm2rl9 decomposed gsvm2rl12 decomposed neos-619167 decomposed gsvm2rl11 decomposed
Name gsvm2rl3 [MIPLIB] gsvm2rl9 [MIPLIB] gsvm2rl12 [MIPLIB] neos-619167 [MIPLIB] gsvm2rl11* [MIPLIB]
Rank / ISS The image-based structural similarity (ISS) metric measures the Euclidean distance between the image-based feature vectors for the query instance and all model groups. A smaller ISS value indicates greater similarity.
1 / 0.422 2 / 0.466 3 / 0.505 299 / 1.348 3* / 0.505*
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIPLIB top 5.
gsvm2rl3 raw gsvm2rl9 raw gsvm2rl12 raw neos-619167 raw gsvm2rl11 raw

Instance Summary

The table below contains summary information for gsvm2rl5, the five most similar instances to gsvm2rl5 according to the MIC, and the five most similar instances to gsvm2rl5 according to MIPLIB 2017.

INSTANCE SUBMITTER DESCRIPTION ISS RANK
Parent Instance gsvm2rl5 [MIPLIB] Toni Sorrell 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 0.000000 -
MIC Top 5 gsvm2rl3 [MIPLIB] Toni Sorrell 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 0.421542 1
gsvm2rl9 [MIPLIB] Toni Sorrell 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 0.465966 2
gsvm2rl12 [MIPLIB] Toni Sorrell 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 0.504636 3
mik-250-20-75-5 [MIPLIB] MIPLIB submission pool Imported from the MIPLIB2010 submissions. 0.554486 4
neos-2746589-doon [MIPLIB] Jeff Linderoth (None provided) 0.933947 5
MIPLIB Top 5 gsvm2rl3 [MIPLIB] Toni Sorrell 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 0.421542 1
gsvm2rl9 [MIPLIB] Toni Sorrell 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 0.465966 2
gsvm2rl12 [MIPLIB] Toni Sorrell 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 0.504636 3
neos-619167 [MIPLIB] NEOS Server Submission Imported from the MIPLIB2010 submissions. 1.347891 299
gsvm2rl11* [MIPLIB] Toni Sorrell 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 0.504636* 3*


gsvm2rl5: Instance-to-Model Comparison Results

Model Group Assignment from MIPLIB: supportvectormachine
Assigned Model Group Rank/ISS in the MIC: 1 / 1.141

MIC Top 5 Model Groups

These are the 5 model group composite (MGC) images that are most similar to the decomposed CCM image for the query instance, according to the ISS metric.

These are model group composite (MGC) images for the MIC top 5 model groups.
Model group: supportvectormachine Model group: mik_250 Model group: bc Model group: neos-pseudoapplication-4 Model group: square
Name supportvectormachine mik_250 bc neos-pseudoapplication-4 square
Rank / ISS The image-based structural similarity (ISS) metric measures the Euclidean distance between the image-based feature vectors for the query instance and all other instances. A smaller ISS value indicates greater similarity.
1 / 1.141 2 / 1.226 3 / 1.654 4 / 1.811 5 / 1.875

Model Group Summary

The table below contains summary information for the five most similar model groups to gsvm2rl5 according to the MIC.

MODEL GROUP SUBMITTER DESCRIPTION ISS RANK
MIC Top 5 supportvectormachine Toni Sorrell 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 1.141113 1
mik_250 MIPLIB submission pool Imported from the MIPLIB2010 submissions. 1.225829 2
bc MIPLIB submission pool Imported from the MIPLIB2010 submissions. 1.653703 3
neos-pseudoapplication-4 Jeff Linderoth (None provided) 1.811391 4
square Sascha Kurz Squaring the square For a given integer n, determine the minimum number of squares in a tiling of an \\(n\\times n\\) square using using only integer sided squares of smaller size. (Although the models get quite large even for moderate n, they can be solved to optimality for all \\(n \\le 61\\), while challenging the MIP solver, especially the presolver.) 1.875080 5


* gsvm2rl11 is a duplicate of gsvm2rl12.

Updated August 16, 2019