public enum TMDDataFormat
MD matrix data type.
Values
| Name | 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. |
| mdFormatRaw | In this case, dissimilarities matrix is calculated by using Dew.Stats.Units.Statistics.PairwiseDistance routine. |
| 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. |