It computes pairwise distance for feature vectors.
y = pdist(x)
y = pdist(x,dtype)
y = pdist(x,dtype,p)
An 2-d array representing a matrix of feature vectors.
A string of three or more characters representing the name of the distance type to be applied. By default its value is 'euc' for Euclidean distance.
An integer used mainly for Minkowski distance. By default, its value is 2 correspoding to Euclidean distance.
A vector of length n*(n-1)/2 for an input array of feature vectors having n rows.
It computes pairwise distance between rows of an input array representing a matrix of feature vectors. The type of the distance measure used in computing pairwise distance is specified in the second argument given as a string of three or more characters. Following is the list of possible values of the second parameter dtype. Value of dtype Distance Measure 'che' Chebyshev distance 'cit' City block distance ( Manhattan distance) 'cor' Correlation 'cos' Cosine distance 'euc' Euclidean distance 'ham' Hamming distance 'jac' Jaccard distance 'mah' Mahalanobis distance 'min' Minkowski distance 'seu' Standardized Eulcidean distance The third parameter p is mainly used for minkowski distance. If p==1, it becomes City Block distance and if p=2 (default) it becomes Eculidean distance. For larger and larger values of p, it approaches to Chebyshev distance.
// Random array x=rand(6,2); // Pairwise Equildean distance measure y=pdist(x), y=pdist(x,'euc') // Eculidean distance using Minkowski ditance y=pdist(x,'min',2) // standard Euclidean measure y1=pdist(x,'seu') | ![]() | ![]() |