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Home › Software › BioNumerics › Features › Multi-Dimensional Scaling (MDS)

Multi-Dimensional Scaling (MDS)

Multi-Dimensional Scaling (MDS), sometimes also called Principal Coordinates Analysis (PCoA), is a non-hierarchic grouping method. Rather than starting from the data set as Principal Components Analysis (PCA) does, MDS uses the similarity matrix as input, which has the advantage over PCA that it can be applied directly to pairwise-compared banding patterns.

3D representation of an MDS

For MDS, the same three-dimensional graphs and viewing tools are available as for PCA and discriminant analysis.

Required modules: 
Dimensioning and Matrix Mining module
See movie: 

Principal components analysis and discriminant analysis on a character data set

File 3 Principal components analysis and discriminant analysis on a character data set.mp4
  • Read more about Principal components analysis and discriminant analysis on a character data set

Principal components analysis and discriminant analysis on a fingerprint data set

File 11 Principal components analysis and discriminant analysis on a fingerprint data set.mp4
  • Read more about Principal components analysis and discriminant analysis on a fingerprint data set

Principal components analysis on a spectrum data set

File 4 Principal components analysis on a spectrum data set.mp4
  • Read more about Principal components analysis on a spectrum data set
See tutorial: 
Calculating a PCA and an MDS on a fingerprint data set
Calculating a PCA and MDS on a character data set
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BioNumerics Seven features

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