That AI consultant said my dataset was too clean, turns out he was right

Guy from a startup meetup told me I was wasting time scrubbing every null value out of my training data. Ran a model on purpose after he left and it actually performed better with some missing fields included. Has anyone else found that messy real-world data works better for certain use cases?

2 comments

2 Comments

black.patricia15d ago

Too clean" datasets, huh. I get the theory but most real world data is a mess and training on scrubbed stuff can miss that. Saying it performs better with missing fields feels like an excuse to skip proper handling, not a genuine improvement.

dakotam1715d ago

Wait, you're saying people think a model actually performs better with missing data? That sounds backwards to me, like claiming a car runs smoother with a flat tire.