Self-similarity matrix
A self-similarity matrix is like a big diagram that helps to find similarities between two sets of data. It looks like a grid with rows and columns. Each row and column in the grid are numbered. For example, if there are 5 rows and 5 columns, the rows and columns would be numbered 1-5.
Within each row or column, there is a number that tells how closely related that row or column is to every other row or column. For example, if two rows are very similar, then they might have a number that is close to 1. If the rows are not very similar at all, then they might have a number that is close to 0.
Overall, the self-similarity matrix helps people to see how closely related different pieces of data are to each other.
Within each row or column, there is a number that tells how closely related that row or column is to every other row or column. For example, if two rows are very similar, then they might have a number that is close to 1. If the rows are not very similar at all, then they might have a number that is close to 0.
Overall, the self-similarity matrix helps people to see how closely related different pieces of data are to each other.
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