Name
Abstract | ||
|---|---|---|
In this paper we present two novel multivariate time series representations to classify physiological data of different lengths. The representations may be applied to any group of multivariate time series data that examine the state or health of an entity. Multivariate Bag-of-Patterns and Stacked Bags of-Patterns improve on their univariate counterpart, inspired by the bag-of-words model, by using multiple time series and analyzing the data in a multivariate fashion. We also borrow techniques from the natural language processing domain such as term frequency and inverse document frequency to improve classification accuracy. We introduce a technique named inverse frequency and present experimental results on classifying patients who have experienced acute episodes of hypotension. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ICDMW.2011.174 | ICDM Workshops |
Keywords | Field | DocType |
information retrieval,medical computing,natural language processing,pattern classification,physiology,time series,inverse frequency,multivariate bag-of-words models,multivariate fashion,multivariate time series representations,natural language processing,physiological data classification,stacked bags of-patterns,Multivariate Bag-of-Patterns,Stacked Bags-of-Patterns,classification,clincal informatics,multivariate time series | Bag-of-words model,Data mining,Inverse,Time series,tf–idf,Pattern recognition,Computer science,Multivariate statistics,Artificial intelligence,Univariate,Machine learning | Conference |
Citations | PageRank | References |
6 | 0.51 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Patricia Ordonez | 1 | 25 | 3.63 |
| Tom Armstrong | 2 | 16 | 3.51 |
| Tim Oates | 3 | 1069 | 190.77 |
| Jim Fackler | 4 | 16 | 1.86 |