Improved boosting algorithms using confidence-rated predictions
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Fast training of support vector machines using sequential minimal optimization
Advances in kernel methods
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Multidimensional curve classification using passing—through regions
Pattern Recognition Letters - Special issue on pattern recognition in practice VI
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
On-Line Handwriting Recognition with Support Vector Machines " A Kernel Approach
IWFHR '02 Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)
Local feature extraction and its applications using a library of bases
Local feature extraction and its applications using a library of bases
Generalized feature extraction for structural pattern recognition in time-series data
Generalized feature extraction for structural pattern recognition in time-series data
Interval and dynamic time warping-based decision trees
Proceedings of the 2004 ACM symposium on Applied computing
Temporal classification: extending the classification paradigm to multivariate time series
Temporal classification: extending the classification paradigm to multivariate time series
Training ν-Support Vector Classifiers: Theory and Algorithms
Neural Computation
Boosting interval based literals
Intelligent Data Analysis
A brief introduction to boosting
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Classification of multivariate time series using two-dimensional singular value decomposition
Knowledge-Based Systems
Classification of multivariate time series using locality preserving projections
Knowledge-Based Systems
Recognising Human Emotions from Body Movement and Gesture Dynamics
ACII '07 Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction
Shape-based template matching for time series data
Knowledge-Based Systems
A shapelet transform for time series classification
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Alternative quality measures for time series shapelets
IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
A sub-block-based eigenphases algorithm with optimum sub-block size
Knowledge-Based Systems
A sparse kernel algorithm for online time series data prediction
Expert Systems with Applications: An International Journal
A time series forest for classification and feature extraction
Information Sciences: an International Journal
Classification of time series by shapelet transformation
Data Mining and Knowledge Discovery
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In previous works, a time series classification system has been presented. It is based on boosting very simple classifiers, formed only by one literal. The used literals are based on temporal intervals. The obtained classifiers were simply a linear combination of literals, so it is natural to expect some improvements in the results if those literals were combined in more complex ways. In this work we explore the possibility of using the literals selected by the boosting algorithm as new features, and then using a SVM with these metafeatures. The experimental results show the validity of the proposed method.