I am trying to do some (k-means) clustering on a very large matrix. The matrix is approximately 500000 rows x 4000 cols yet very sparse (only a c开发者_JAVA技巧ouple of \"1\" values per row). I want
I am trying to write a bag of features system image recognition system. One step in the algorithm is to take a larger number of small image patches (say 7x7 or 11x11 pixels) and try to cluster them in
I recently started experimenting with the bigan开发者_高级运维alytics package for R. I ran into a problem however...
I wish to create a \"subtree\" from an hclust object. For example, let\'s say I have the following object:
I came across this interesting website, with an idea of a way to visualize a clustering algorithm called \"Clustergram\":
I would like to know K-means is best suited for clustering of which type of data? 开发者_开发技巧
How can I compute the z-score for matrices in Python? Suppose I have the array: a = array([[1,2,3], [30,35,36],
How can I plot a dendrogram right on top of a matrix of values, reordered appropriately to reflect the clustering, in Python?An example is the following figure:
When I say coordinates I mean latitude and longitude coordinates of earth. I w开发者_开发技巧ant to determine if a set of coordinates are within the same area (my cutoff is 200 miles). I\'ve been goog
I\'m trying to compute clusters on a set of points in Python, using GeoDjango. The problem: Given a set of points, output a set of clusters of those points.
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