%0 Conference Paper %1 Antaresti_2011 %A Antaresti, Tieta %A Fanany, Mohamad Ivan %A Arymurthy, Aniati Murni %B 2011 Sixth International Conference on Digital Information Management %D 2011 %I Institute of Electrical and Electronics Engineers (IEEE) %K myown %R 10.1109/icdim.2011.6093359 %T Maintaining imbalance highly dependent medical data using dirichlet process data generation %U http://dx.doi.org/10.1109/ICDIM.2011.6093359 %X The existence of imbalanced data between one class and another class is an important issue to be considered in a classification problem. One of the well-known data balancing technique is the artificial oversampling, which increase the size of datasets. In this research, multinomial classification was applied to classify some recorded features obtained from a single ECG (electrocardiograph) sensor. Therefore, a Dirichlet process, a dirichlet distribution of cumulative distribution function of each data partition, was needed to model the distribution of the new generated data by also considering the statistical properties of the previous data. Data balancing process had given the result of 77.21% classification accuracy (CA), and 90.9% area under ROC curve (AUC).

@inproceedings{Antaresti_2011, abstract = {The existence of imbalanced data between one class and another class is an important issue to be considered in a classification problem. One of the well-known data balancing technique is the artificial oversampling, which increase the size of datasets. In this research, multinomial classification was applied to classify some recorded features obtained from a single ECG (electrocardiograph) sensor. Therefore, a Dirichlet process, a dirichlet distribution of cumulative distribution function of each data partition, was needed to model the distribution of the new generated data by also considering the statistical properties of the previous data. Data balancing process had given the result of 77.21% classification accuracy (CA), and 90.9% area under ROC curve (AUC).}, added-at = {2016-10-29T09:40:29.000+0200}, author = {Antaresti, Tieta and Fanany, Mohamad Ivan and Arymurthy, Aniati Murni}, biburl = {https://www.bibsonomy.org/bibtex/2e19d76af5e8ed7ec8fd80b43c846e907/fanany}, booktitle = {2011 Sixth International Conference on Digital Information Management}, doi = {10.1109/icdim.2011.6093359}, interhash = {710e3a3cae5f806f98b257eca2392b15}, intrahash = {e19d76af5e8ed7ec8fd80b43c846e907}, keywords = {myown}, month = sep, publisher = {Institute of Electrical and Electronics Engineers ({IEEE})}, timestamp = {2016-10-29T09:40:29.000+0200}, title = {Maintaining imbalance highly dependent medical data using dirichlet process data generation}, url = {http://dx.doi.org/10.1109/ICDIM.2011.6093359}, year = 2011 }