Feature vectors distance metrics

When, say, infrared or mass spectra can be reduced to binary strings indicating the presence or absence of peaks or other features, the Hamming distance metric is simple to implement. In such cases it provides a value of differing bits in the binary pattern and is equivalent to performing the exclusive-OR function between the vectors. The Hamming distance is a popular choice in spectral... 

Unsupervised classification - Cluster analysis. Unsupervised classification or cluster analysis is a way to find natural patterns in a data set. There are no independent true answers that can guide the classification and we are therefore restricted to construct a set of criteria or general rules that can highlight the interesting patterns in a data set. A data set consists usually of a set of objects that each are characterised by a feature vector x. To find patterns it is important to establish to what degree vectors are similar to each other. Similarity is often defined using a distance metric between object i and j... 

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