DBSCAN in scikit-learn of Python: save the cluster points in an array
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Solution 1
The first cluster is X[labels == 0]
, etc.:
clusters = [X[labels == i] for i in xrange(n_clusters_)]
and the outliers are
outliers = X[labels == -1]
Solution 2
What do you mean by "of each cluster"?
In DBSCAN, clusters are not represented as centroids as in k-means, so there is no obvious representation of the cluster except its members. You already have the x and y position of the cluster members, as they are the input data.
So I'm not sure what the question is.
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Gianni Spear
Updated on July 09, 2022Comments
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Gianni Spear almost 2 years
following the example Demo of DBSCAN clustering algorithm of Scikit Learning i am trying to store in an array the x, y of each clustering class
import numpy as np from sklearn.cluster import DBSCAN from sklearn import metrics from sklearn.datasets.samples_generator import make_blobs from sklearn.preprocessing import StandardScaler from pylab import * # Generate sample data centers = [[1, 1], [-1, -1], [1, -1]] X, labels_true = make_blobs(n_samples=750, centers=centers, cluster_std=0.4, random_state=0) X = StandardScaler().fit_transform(X) xx, yy = zip(*X) scatter(xx,yy) show()
db = DBSCAN(eps=0.3, min_samples=10).fit(X) core_samples = db.core_sample_indices_ labels = db.labels_ n_clusters_ = len(set(labels)) - (1 if -1 in labels else 0) print n_clusters_ 3
I'm trying to understand the DBSCAN implementation by scikit-learn, but from this point I'm having trouble. The number of cluster is 3 (n_clusters_) and I wish to store the x, y of each cluster in an array
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Gianni Spear almost 11 yearshey Andreas, sorry if i was not clear. If you see in figure 2 each points (x, y) has a different color due to the cluster (e.g., 3 clusters in the example and back dots are noise). I wish to have an array with 3 blocks. Each block store the x, y points values of that cluter.
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user3378649 about 10 yearsYou have x and y position of the cluster members, but how can you know in which cluster these points are ?
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GoingMyWay over 6 years@user3378649, there are lables corresponding to its cluster.
dbscan.labels_