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Description 

mdFormatDissimilarities 

Dissimilarities represent the distance between two objects. They may be measured directly or approximated. MDS algorithms use the dissimilarities directly. A dissimilarity matrix is always symmetrical and with zero main diagonal. 

mdFormatSimilarities 

Similarities represent how close (in some sense) two objects are. Similarities must obey the rule:
similarity(i,j) <= similarity(i,i) and similarity(j,j)
for all i and j. Similarity matrices are symmetrical. Similarities are converted to dissimilarities by the following relation:
d(i,j) = Sqrt[s(i,i) + s(j,j) -2*s(i,j)]
where d(i,j) represents a dissimilarity and s(i,j) represents a similarity. In case your data consists of standard measures rather than dissimilarities or similarities, you can create a similarity matrix by creating the correlation matrix. 

mdFormatRaw 

In this case, dissimilarities matrix is calculated by using PairwiseDistance routine.