I am working on predictive maintenance and get temperature data from assets. In few months or few days asset remains down and we do not get temperature value. In this scenario i cannot fill data with missing value techniques. Also cannot give some number because even 0 and -1 are valid values for temperature. How to deal with such data?
I am thinking of putting very big value for such columns which is not possible as temperature. Please suggest.
I suppose 6 months fake value is of no use, if we consider data relationship, else lead to wrong prediction.
Data cannot be filtered or filled with any measure of central tendency in above scenario. Missing data can be imputed in this scenario using following techniques: