Jan-27-2023, 04:20 PM
I am struggling with the problem I am facing: I have a dataset of different products (Cars) that have certain Work Orders open at a given time. I know from historical data how much time this work in TOTAL has caused. Now I want to predict it for another Car (e.g. Car 3). I do not know the hours caused by a single item, only by this set of items together, thats what I mean with TOTAL hours.
Which type of algorithm, regression shall I use for this?
My idea was to transform this row based dataset into column based with binary values e.g. Brake: 0/1, Screen 0/1.. But then I will have lots of Inputs as the number of possible Inputs is 100-200..
Which type of algorithm, regression shall I use for this?
My idea was to transform this row based dataset into column based with binary values e.g. Brake: 0/1, Screen 0/1.. But then I will have lots of Inputs as the number of possible Inputs is 100-200..
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