Multivariate time Series classification - One class


I need your help with time series classification. I have measurements of different medical parameters for patients captured at every one hour. The output label is whether the patient has Acute Kidney Injury(AKI) or not. Based on the first 12 hour data, we should find out whether the patient has the risk of suffering from AKI or not (After 12 hours). I guess this falls under classification approach (Sequence Classification). However I have only one label (AKI == 0). So should this be considered as Anomaly detection in Time series or Sequence classification? Since I have more than 100 patients data for 12 hour (100 * 12 datapoints with multiple input variables), how do I retain the time factor? As there is only one class, how do I do the training? I am quite stuck as I am quite new to this area. Can you please share your insights/ guide me as to how to approach this problem/direct me to the appropriate resource/sample project?

The Great

Posted 2018-12-25T15:42:18.000

Reputation: 1 539

You are right: this is a sequence classification problem. I suggest to use the application of a neural network with a special network architecture: a combination of convolutional neural network layers (CNN) and recurrent networks (RNN). This is a typical network architecture in this field. – Wolfgang123 – 2019-01-17T17:08:26.460

If you have only one class in the training set you can try methods of anomaly detection in time series. You don't have the opposite class examples to apply the binary classification. – wind – 2019-01-18T10:12:18.603

No answers