Results 251 to 260 of about 576,901 (299)

Early classification on multivariate time series

Neurocomputing, 2015
Multivariate time series (MTS) classification is an important topic in time series data mining, and has attracted great interest in recent years. However, early classification on MTS data largely remains a challenging problem. To address this problem without sacrificing the classification performance, we focus on discovering hidden knowledge from the ...
Guoliang He, Yong Duan, Rong Peng, Xiaoyuan Jing, Tieyun Qian, Lingling Wang   +5 more
openaire   +3 more sources

Time Series Classification at Scale

, 2019
This thesis develops scalable algorithms and techniques to classify large amount of time series data. Nowadays, many real-world applications are generating huge amount of time series data. This wealth of data is required to create finer and more accurate classification models that allow us to learn from the data.
CHANG WEI TAN (6527420)
openaire   +2 more sources

Scalable and Accurate Time Series Classification

, 2022
This thesis focuses on time series classification, which aims to develop algorithms that learn to categorize temporally ordered data. It is an important area of machine learning research with a diverse range of applications, such as the classification of satellite images, medical and human activity data.
AHMED SHIFAZ (11925272)
openaire   +2 more sources

Early classification on time series

Knowledge and Information Systems, 2011
In this paper, we formulate the problem of early classification of time series data, which is important in some time-sensitive applications such as health informatics. We introduce a novel concept of MPL (minimum prediction length) and develop ECTS (early classification on time series), an effective 1-nearest neighbor classification method.
Zhengzheng Xing, Jian Pei 0001, Philip S. Yu   +2 more
openaire   +1 more source

Unsupervised time series classification

Signal Processing, 1995
Abstract In this paper a scheme for unsupervised probabilistic time series classification is detailed. The technique utilizes autocorrelation terms as discriminatory features and employs the Volterra Connectionist Model (VCM) to transform the multi-dimensional feature information of each training vector to a one-dimensional classification space. This
Jebu J. Rajan, Peter J. W. Rayner
openaire   +1 more source

On the Blind Classification of Time Series

2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007
We propose a cord distance in the space of dynamical models that takes into account their dynamics, including transients, output maps and input distributions. In data analysis applications, as opposed to control, the input is often not known and is inferred as part of the (blind) identification.
Alessandro Bissacco, Stefano Soatto
openaire   +1 more source

Time series envelopes for classification

2010 5th IEEE International Conference Intelligent Systems, 2010
In this paper we considered a streaming data classification problem. First we introduced a concept of upper and lower envelopes of time series in order to reduce dimensionality of them. Next we merged machine learning tools like feedforward neural networks for selection principal attributes as well as decision rules of the form if … then … for time ...
Maciej Krawczak, Grazyna Szkatula
openaire   +1 more source

Minimizing response time in time series classification

Knowledge and Information Systems, 2015
Providing a timely output is one of the important criteria in applications of time series classification. Recent studies have been motivated to explore models of early prediction, prediction based on truncated temporal observations. The truncation of input improves the response time, but generally reduces the reliability of the prediction.
Shin Ando, Einoshin Suzuki
openaire   +1 more source

Compressed learning for time series classification

2016 IEEE International Conference on Big Data (Big Data), 2016
The time series classification has been studied for various applications in the last decades. In the time series classification problem, we decide the class information based on a small piece of the time series inputs. In general, the approaches to time series classification can be categorized into three types, distance-based, model-based, and feature ...
Yuh-Jye Lee, Hsing-Kuo Pao, Shueh-Han Shih, Jing-Yao Lin, Xin-Rong Chen   +4 more
openaire   +1 more source

Classification of time series

2021
Το πρόβλημα της κατηγοριοποίησης είναι ένα διαχρονικό και παράλληλα επίκαιρο πρόβλημα που καλείται να λύσει ένας αλγόριθμος. Η κατηγοριοποίηση μπορεί να γίνει σε πολλούς τύπους δεδομένων. Τα τελευταία χρόνια με την αύξηση της ταχύτητας των δικτύων και της δυνατότητας αποθήκευσης δεδομένων, οι χρονοσειρές εισήλθαν δυναμικά στο πεδίο της εξόρυξης ...
openaire   +1 more source