Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Pattern-Based Analysis of Time Series: Estimation   While Internet of Things (IoT) devices and sensors create continuous streams
of information, Big Data infrastructures are deemed to handle the influx of
data in real-time. One type of such a continuous stream of information is time
series data. Due to the richness of information in time series and inadequacy
of summary statistics to encapsulate structures and patterns in such data,
development of new approaches to learn time series is of interest. In this
paper, we propose a novel method, called pattern tree, to learn patterns in the
times-series using a binary-structured tree. While a pattern tree can be used
for many purposes such as lossless compression, prediction and anomaly
detection, in this paper we focus on its application in time series estimation
and forecasting. In comparison to other methods, our proposed pattern tree
method improves the mean squared error of estimation.

26
The categories of this paper are: bayes-an
3
The categories of this paper are: physics
7
The categories of this paper are: hep-th
27
The categories of this paper are: comp-gas
31
The categories of this paper are: ao-sci
25
The categories of this paper are: patt-sol
14
The categories of this paper are: math-ph
15
The categories of this paper are: nucl-ex
8
The categories of this paper are: hep-ex
32
The categories of this paper are: atom-ph
13
The categories of this paper are: quant-ph
21
The categories of this paper are: adap-org
10
The categories of this paper are: q-bio
11
The categories of this paper are: hep-lat
17
The categories of this paper are: q-fin
4
The categories of this paper are: cond-mat