Results 221 to 230 of about 19,696,345 (257)

Embedding Time Series Data for Classification

2005
We propose an approach to embed time series data in a vector space based on the distances obtained from Dynamic Time Warping (DTW), and to classify them in the embedded space. Under the problem setting in which both labeled data and unlabeled data are given beforehand, we consider three embeddings, embedding in a Euclidean space by MDS, embedding in a ...
Akira Hayashi, Yuko Mizuhara, Nobuo Suematsu   +2 more
openaire   +1 more source

Stacking for multivariate time series classification

Pattern Analysis and Applications, 2013
This work presents a novel approach to multivariate time series classification. The method exploits the multivariate structure of the time series and the possibilities of the stacking ensemble method. The basics of the method may be described in three steps: first, decomposing the multivariate time series on its constituent univariate time series ...
Oscar J. Prieto, Carlos J. Alonso-González, Juan José Rodríguez Diez   +2 more
openaire   +1 more source

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
openaire   +2 more sources

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
openaire   +1 more source

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
openaire   +1 more source

Sequential classification of MODIS time series

2012 IEEE International Geoscience and Remote Sensing Symposium, 2012
In this paper a sequential time-varying maximum likelihood classifier is applied on coarse resolution MODIS surface reflectance data. It is shown that good class separability can be obtained after considering only one year of data. Finally it is shown that after NDVI, band 2 has the highest separability of all the MODIS land bands, and band 6 has the ...
Trienko L. Grobler, Etienne R. Ackermann, Augustinus J. van Zyl, Waldo Kleynhans, Brian P. Salmon, Jan C. Olivier   +5 more
openaire   +1 more source

Time series classification with their image representation

Neurocomputing
The study is concerned with the problem of classification of multivariate time series using convolutional neural networks (CNNs). As CNNs regard inputs in the form of images, an original image -like format of temporal data is proposed. Along this line, several design alternatives are studied by forming images with the two corresponding coordinates ...
Wladyslaw Homenda, Agnieszka Jastrzebska, Witold Pedrycz, Mariusz Wrzesien   +3 more
openaire   +3 more sources

Time Series Classification with Representation Ensembles

2015
Time series has attracted much attention in recent years, with thousands of methods for diverse tasks such as classification, clustering, prediction, and anomaly detection. Among all these tasks, classification is likely the most prominent task, accounting for most of the applications and attention from the research community.
Rafael Giusti, Diego Furtado Silva, Gustavo E. A. P. A. Batista   +2 more
openaire   +1 more source

Model-Based Time Series Classification

2014
We propose MTSC, a filter-and-refine framework for time series Nearest Neighbor (NN) classification. Training time series belonging to certain classes are first modeled through Hidden Markov Models (HMMs). Given an unlabeled query, and at the filter step, we identify the top K models that have most likely produced the query.
Alexios Kotsifakos, Panagiotis Papapetrou   +1 more
openaire   +2 more sources

Classification of time series by shapelet transformation

Data Mining and Knowledge Discovery, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jon Hills, Jason Lines, Edgaras Baranauskas, James Mapp, Anthony J. Bagnall   +4 more
openaire   +4 more sources