how to draw dendrogram from similarity matrix
I take three matrices to compare. Each of them is 5x6. I originally wanted to utilize hierarchical clustering to cluster the matrices, such that the most similar matrices are grouped, given a threshold of similarity.
I could not notice any such functions in python, and then I implemented the altitude measure by paw, (p-norm where p=2). Now I have a 3x3 distance matrix (which I believe is likewise a similarity matrix in this example).
I am now trying to produce a dendrogram. This is my code, and this is what is wrong. I desire to produce a graph (a dendrogram if possible) that shows clusters of the matrices that are virtually like. Of matrices 0,i,2, 0 and two are the same and should be clustered together showtime, and i is dissimilar.
The altitude matrix looks like this:
> 0 one two 0 0.0 ii.0 3.85e-16 one two.0 0.0 2.0 two three.85e-sixteen 2.0 0.0
Code:
from scipy.cluster.hierarchy import dendrogram import matplotlib.pyplot as plt import numpy equally np from scipy.cluster.hierarchy import linkage mat = np.assortment([[0.0, 2.0, iii.8459253727671276e-xvi], [ii.0, 0.0, two.0], [three.8459253727671276e-16, 2.0, 0.0]]) dist_mat = mat linkage_matrix = linkage(dist_mat, "single") dendrogram(linkage_matrix, color_threshold=1, labels=["0", "one", "two"],show_leaf_counts=True) plt.title=("test") plt.show()
This is the output:
What is the meaning of the linkage(dist_mat, 'single')? I would have assumed the output graph to wait something like this, where the distance is 2.0 between 0 and 1 (for example).
Are in that location amend means to represent these data? Is there a function that could have in several matrices instead of points, to compare and course a altitude matrix, then cluster? I am open to other suggestions on how to visualize the differences between these matrices.
Source: https://stackoverflow.com/questions/41416498/dendrogram-or-other-plot-from-distance-matrix
Posted by: gallawaynoter1965.blogspot.com
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