similarity matrix

Page numbers are for draft copy at present; they will be replaced with correct numbers when final book is formatted. Chapter numbers are correct and will not change now.

If we have a set of N data items d_i and calculate a simiarity metric between each pair (d_i,d_k), 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:
      (d_i,d_k)   =   (d_k,d_i)
This means that the similarity matrix is a symmetric matrx ... and thus have lots of nice mathematical properties that the algorithms utilise.

Used on Chap. 6: page 121; Chap. 7: pages 134, 135; Chap. 21: page 527