sapientinc/sudoku-extreme

Dataset

Hardest Sudoku Puzzle Dataset V2

35

stars

3

commits

2

linked in READMEs

Oct 17, 2024

updated

README

Hardest Sudoku Puzzle Dataset V2

This dataset contains a mixture of easy and very hard Sudoku puzzles collected from the Sudoku community.

Dataset Composition

Sources

Easy Puzzles (1.1M)

  • puzzles0_kaggle
  • puzzles1_unbiased
  • puzzles2_17_clue

Hard Puzzles (3.1M)

  • puzzles3_magictour_top1465
  • puzzles4_forum_hardest_1905
  • puzzles6_forum_hardest_1106
  • ph_2010/01_file1.txt

Dataset Characteristics

  • All puzzles have been exact-deduped and randomly permuted by row, column, box, and digit.
  • Each puzzle is guaranteed to have a unique solution.
  • Puzzles in the train set are mathematically inequivalent to those in the test set.

Dataset Structure

  • Train set: train.csv (3.8M examples)
  • Test set: test.csv (423k examples)

Puzzles and solutions are flattened in row-major order. Rating is evaluated by number of backtracks needed by [tdoku solver]((https://github.com/t-dillon/tdoku) required to solve the puzzle (higher is harder).

Usage Guidelines

  1. Train models using only the train set.
  2. Evaluate models on the test set using exact accuracy (all numbers must be correct).

Contributors

imone

3 commits

sapientinc/sudoku-extreme

Dataset

Hardest Sudoku Puzzle Dataset V2

35

stars

3

commits

2

linked in READMEs

Oct 17, 2024

updated

README

Hardest Sudoku Puzzle Dataset V2

This dataset contains a mixture of easy and very hard Sudoku puzzles collected from the Sudoku community.

Dataset Composition

Sources

Easy Puzzles (1.1M)

  • puzzles0_kaggle
  • puzzles1_unbiased
  • puzzles2_17_clue

Hard Puzzles (3.1M)

  • puzzles3_magictour_top1465
  • puzzles4_forum_hardest_1905
  • puzzles6_forum_hardest_1106
  • ph_2010/01_file1.txt

Dataset Characteristics

  • All puzzles have been exact-deduped and randomly permuted by row, column, box, and digit.
  • Each puzzle is guaranteed to have a unique solution.
  • Puzzles in the train set are mathematically inequivalent to those in the test set.

Dataset Structure

  • Train set: train.csv (3.8M examples)
  • Test set: test.csv (423k examples)

Puzzles and solutions are flattened in row-major order. Rating is evaluated by number of backtracks needed by [tdoku solver]((https://github.com/t-dillon/tdoku) required to solve the puzzle (higher is harder).

Usage Guidelines

  1. Train models using only the train set.
  2. Evaluate models on the test set using exact accuracy (all numbers must be correct).

Contributors

imone

3 commits