I have a dataset of diabetes patients and I am trying to predict the next blood glucose level. I have attached an image below and I have about 1600 records in that csv file containing data of 10 patients. Each patient is uniquely identified by the Id column and the Glucose_t-1 means the glucose value in which the patient had before the current reading(Glucose_t) likewise this apply to Glucose_t-2 and Glucose_t-3. And same applies to the Insulin_t-1,Insulin_t-2. The event column is the Glycemic event in which the current reading of the blood glucose value falls to. For example,
- blood glucose value <= 70 then 0,
- 70< blood glucose value <=180 then 1,
- blood glucose value > 180 then 2.
I have applied different regression algorithms like Logisitic Regression, Random Forest Regression and so on but I was unable to predict the Glucose_t value accurately. The accuracy comes to 0.008.. which is very depressing :(. Please any help to improve the accuracy of will be greatly appreciated. Thanks.