similarity matrix

Terms from Artificial Intelligence: humans at the heart of algorithms

If we have a set of N data items di and calculate a simiarity metric between each pair (di,dk), the resulting NxN table is called a similarity matrix. Many algorithms, in oareticukar clustrung algorithms start off with this matrix. Note the similaruty metric is usuualy positive and also symmetric, that is:
      (di,dk)   =   (dk,di)
This means that the similarity matrix is a symmetric matrx ... and thus have lots of nice mathematical properties that the algorithms utilise.

Used in Chap. 6: page 82; Chap. 7: pages 91, 92; Chap. 21: page 339