Models of incremental concept formation
Artificial Intelligence
Generating Accurate Rule Sets Without Global Optimization
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Cluster ensembles --- a knowledge reuse framework for combining multiple partitions
The Journal of Machine Learning Research
Combining Multiple Weak Clusterings
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Improvements to Platt's SMO Algorithm for SVM Classifier Design
Neural Computation
Working Set Selection Using Second Order Information for Training Support Vector Machines
The Journal of Machine Learning Research
Consensus unsupervised feature ranking from multiple views
Pattern Recognition Letters
Aggregating inconsistent information: Ranking and clustering
Journal of the ACM (JACM)
Robust projective filtering of time-warped ECG beats
Computer Methods and Programs in Biomedicine
Adaptive neuro-fuzzy inference system for classification of ECG signals using Lyapunov exponents
Computer Methods and Programs in Biomedicine
Numerical Mathematics and Computing
Numerical Mathematics and Computing
Computer Methods and Programs in Biomedicine
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
Classification of the electrocardiogram signals using supervised classifiers and efficient features
Computer Methods and Programs in Biomedicine
Artificial Intelligence in Medicine
Data Mining: Practical Machine Learning Tools and Techniques
Data Mining: Practical Machine Learning Tools and Techniques
Feature extraction for ECG heartbeats using higher order statistics of WPD coefficients
Computer Methods and Programs in Biomedicine
Unsupervised feature relevance analysis applied to improve ECG heartbeat clustering
Computer Methods and Programs in Biomedicine
Cloud-ECG for real time ECG monitoring and analysis
Computer Methods and Programs in Biomedicine
Biomedical time series clustering based on non-negative sparse coding and probabilistic topic model
Computer Methods and Programs in Biomedicine
ECG beat classification using a cost sensitive classifier
Computer Methods and Programs in Biomedicine
Check Your Biosignals Here: A new dataset for off-the-person ECG biometrics
Computer Methods and Programs in Biomedicine
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Accurate and fast approaches for automatic ECG data classification are vital for clinical diagnosis of heart disease. To this end, we propose a novel multistage algorithm that combines various procedures for dimensionality reduction, consensus clustering of randomized samples and fast supervised classification algorithms for processing of the highly dimensional large ECG datasets. We carried out extensive experiments to study the effectiveness of the proposed multistage clustering and classification scheme using precision, recall and F-measure metrics. We evaluated the performance of numerous combinations of various methods for dimensionality reduction, consensus functions and classification algorithms incorporated in our multistage scheme. The results of the experiments demonstrate that the highest precision, recall and F-measure are achieved by the combination of the rank correlation coefficient for dimensionality reduction, HBGF consensus function and the SMO classifier with the polynomial kernel.