I am working on a logistic regression problem for offshore rig automation. One of the predictors is time duration reading from a sensor.
Due to the nature of the sensor (and the automation system), the measured duration --- a continuous value --- concentrates in two regions: one region is 1 second to 10 seconds; another region is 1 minute to 2 hours.
Surely, I can use log pre-processing to make this feature's histogram more like a bell-shape. But in the end, these 2 clusters exist. Also, these 2 clusters exist for a reason, something to do with some valves' status.
I am thinking about treating this continuous feature like a categorical feature: split it into 2 separated features (one for each cluster) , similar to one-hot encoding. However, different from one-hot-encoding, the two new features will be continuous values.
Does this make sense from a theoretical perspective? Can anyone provide some reference for me so I can read up (or google) ?