Dataset Open Access

Synthetic dataset used in "The maximum weighted submatrix coverage problem: A CP approach"

Derval Guillaume; Branders Vincent; Dupont Pierre; Schaus Pierre

Synthetic dataset used in "The maximum weighted submatrix coverage problem: A CP approach".

Includes both the generated datasets as a zip archive and the python script used to generate them.

Each instance is composed of two files in the form

  • XxY_K_O_0xN_AxB_Smatrix.tsv being the matrix to use. Each row on a separate line, with tab-separated cells.
  • XxY_K_O_0xN_AxB_Ssolution.txt giving the implanted solution. One submatrix per line. Then two JSON arrays follow, separated by a tabulation. The first is the list of rows selected in the submatrix, the second the columns.

With:

  • X and Y the size of the matrix
  • K the number of submatrices in the implanted solution
  • O the (minimum) overlap percentage of each submatrix
  • N the sigma used for the background noise
  • A and B the size of the implanted submatrices (subject to noise)

 

Files (1.6 GB)
Name Size
data.zip
md5:8fdc30aa0546ed2b8a520c06b4b387b4
1.6 GB Download
generation.py
md5:4008ea48e3afae4d8466fdb9b9f2f65a
10.5 kB Download
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