Results 161 to 170 of about 20,272,779 (202)

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
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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 ...
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Semi-supervised time series classification

Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining, 2006
The problem of time series classification has attracted great interest in the last decade. However current research assumes the existence of large amounts of labeled training data. In reality, such data may be very difficult or expensive to obtain. For example, it may require the time and expertise of cardiologists, space launch technicians, or other ...
Li Wei 0001, Eamonn J. Keogh
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Efficient Classification of Long Time-Series

2013
Time-series classification has gained wide attention within the Machine Learning community, due to its large range of applicability varying from medical diagnosis, financial markets, up to shape and trajectory classification. The current state-of-art methods applied in time-series classification rely on detecting similar instances through neighboring ...
Josif Grabocka, Erind Bedalli, Lars Schmidt-Thieme   +2 more
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Description and classification of granular time series

Soft Computing, 2014
The study is concerned with a concept and a design of granular time series and granular classifiers. In contrast to the plethora of various models of time series, which are predominantly numeric, we propose to effectively exploit the idea of information granules in the description and classification of time series.
Rami Al-Hmouz, Witold Pedrycz, Abdullah Saeed Balamash, Ali Morfeq   +3 more
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Time Series based Gastropod Classification

2018 10th International Conference on Knowledge and Smart Technology (KST), 2018
This paper presents Series-K, an automatic Gastropod classification system based on Time Series and k-Nearest Neighbor. Species evolve over time. Biologists have discovered, attempted to describe and put them into categories. Our proposed method automatically processes gastropods’ images to help the malacologists accurately identify gastropods into ...
Janya Onpans, Nutthanon Leelathakul, Sunisa Rimcharoen   +2 more
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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
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Fuzzy classification of time series data

2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2013
The problem of classification of time series data is an interesting problem in the field of data mining. Even though several algorithms have been proposed for the problem of time series classification we have developed an innovative algorithm which is computationally fast and accurate in several cases when compared with 1NN classifier. In our method we
Penugonda Ravikumar, V. Susheela Devi
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Piecewise Factorization for Time Series Classification

2016
In the research field of time series analysis and mining, the nearest neighbor classifier (1NN) based on the dynamic time warping distance (DTW) is well known for its high accuracy. However, the high computational complexity of DTW can lead to the expensive time consumption of the classifier.
Qinglin Cai, Ling Chen 0001, Jianling Sun   +2 more
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Cost Sensitive Time-Series Classification

2017
This paper investigates the problem of highly imbalanced time-series classification using shapelets, short patterns that best characterize the target time-series, which are highly discriminative. The current state-of-the-art approach learns generalized shapelets along with weights of the classification hyperplane via a classical cost-insensitive loss ...
Shoumik Roychoudhury, Mohamed F. Ghalwash, Zoran Obradovic   +2 more
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