Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Usage of multiple RTL features for Earthquake prediction   We construct a classification model that predicts if an earthquake with the
magnitude above a threshold will take place at a given location in a time range
30-180 days from a given moment of time. A common approach is to use expert
forecasts based on features like Region-Time-Length (RTL) characteristics. The
proposed approach uses machine learning on top of multiple RTL features to take
into account effects at various scales and to improve prediction accuracy. For
historical data about Japan earthquakes 1992-2005 and predictions at locations
given in this database the best model has precision up to ~ 0.95 and recall up
to ~ 0.98.

17
The categories of this paper are: q-fin
27
The categories of this paper are: comp-gas
34
The categories of this paper are: chem-ph
13
The categories of this paper are: quant-ph
22
The categories of this paper are: chao-dyn
31
The categories of this paper are: ao-sci
36
The categories of this paper are: cmp-lg
4
The categories of this paper are: cond-mat
24
The categories of this paper are: dg-ga
6
The categories of this paper are: astro-ph
12
The categories of this paper are: nucl-th
28
The categories of this paper are: alg-geom
37
The categories of this paper are: supr-con
35
The categories of this paper are: mtrl-th
32
The categories of this paper are: atom-ph
9
The categories of this paper are: nlin