KARDIO: a study in deep and qualitative knowledge for expert systems
KARDIO: a study in deep and qualitative knowledge for expert systems
C4.5: programs for machine learning
C4.5: programs for machine learning
Machine Learning
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Locally adaptive dimensionality reduction for indexing large time series databases
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Feature Extraction, Construction and Selection: A Data Mining Perspective
Feature Extraction, Construction and Selection: A Data Mining Perspective
Time Series Analysis, Forecasting and Control
Time Series Analysis, Forecasting and Control
A Brief Introduction to Boosting
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
A Method for Clustering the Experiences of a Mobile Robot that Accords with Human Judgments
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Local feature extraction and its applications using a library of bases
Local feature extraction and its applications using a library of bases
Supervised classification with temporal data
Supervised classification with temporal data
Temporal classification: extending the classification paradigm to multivariate time series
Temporal classification: extending the classification paradigm to multivariate time series
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
Using decision trees to recognize visual events
AREA '08 Proceedings of the 1st ACM workshop on Analysis and retrieval of events/actions and workflows in video streams
Multivariable stream data classification using motifs and their temporal relations
Information Sciences: an International Journal
Characteristic-based descriptors for motion sequence recognition
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
Visual event recognition using decision trees
Multimedia Tools and Applications
A brief survey on sequence classification
ACM SIGKDD Explorations Newsletter
Time series gene expression data classification via L1-norm temporal SVM
PRIB'10 Proceedings of the 5th IAPR international conference on Pattern recognition in bioinformatics
A review on time series data mining
Engineering Applications of Artificial Intelligence
Classification trees for time series
Pattern Recognition
Segment and combine approach for non-parametric time-series classification
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
Strengthening learning algorithms by feature discovery
Information Sciences: an International Journal
Multivariate stream data classification using simple text classifiers
DEXA'06 Proceedings of the 17th international conference on Database and Expert Systems Applications
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We present a method of constructive induction aimed at learning tasks involving multivariate time series data. Using metafeatures, the scope of attribute-value learning is expanded to domains with instances that have some kind of recurring substructure, such as strokes in handwriting recognition, or local maxima in time series data. The types of substructures are defined by the user, but are extracted automatically and are used to construct attributes.Metafeatures are applied to two real domains: sign language recognition and ECG classification. Using metafeatures we are able to generate classifiers that are either comprehensible or accurate, producing results that are comparable to hand-crafted preprocessing and comparable to human experts.