Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Fast, Linear Time Hierarchical Clustering using the Baire Metric   The Baire metric induces an ultrametric on a dataset and is of linear
computational complexity, contrasted with the standard quadratic time
agglomerative hierarchical clustering algorithm. In this work we evaluate
empirically this new approach to hierarchical clustering. We compare
hierarchical clustering based on the Baire metric with (i) agglomerative
hierarchical clustering, in terms of algorithm properties; (ii) generalized
ultrametrics, in terms of definition; and (iii) fast clustering through k-means
partititioning, in terms of quality of results. For the latter, we carry out an
in depth astronomical study. We apply the Baire distance to spectrometric and
photometric redshifts from the Sloan Digital Sky Survey using, in this work,
about half a million astronomical objects. We want to know how well the (more
costly to determine) spectrometric redshifts can predict the (more easily
obtained) photometric redshifts, i.e. we seek to regress the spectrometric on
the photometric redshifts, and we use clusterwise regression for this.

26
The categories of this paper are: bayes-an
20
The categories of this paper are: acc-phys
24
The categories of this paper are: dg-ga
33
The categories of this paper are: plasm-ph
23
The categories of this paper are: solv-int
9
The categories of this paper are: nlin
7
The categories of this paper are: hep-th
32
The categories of this paper are: atom-ph
0
The categories of this paper are: hep-ph
14
The categories of this paper are: math-ph
4
The categories of this paper are: cond-mat
27
The categories of this paper are: comp-gas
2
The categories of this paper are: math
30
The categories of this paper are: q-alg
10
The categories of this paper are: q-bio
8
The categories of this paper are: hep-ex