Developed a new weighted K-means algorithm for clustering Lego bricks of different shapes and colors.
problem Clustering data with large spread and different scales of measurement.
method Gap-ratio Weighted K-means algorithm, which weights each dimension based on the ratio of the biggest gap to the average of all gaps.
result The gap-ratio K-means algorithm outperformed other variants on the Lego bricks clustering problem and other datasets.