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I wanted to say that I disagreed with you, but then I realized I don't know what you mean by "execution" here, though. This statement "The more complicated a m
by ska 9y ago
I wanted to say that I disagreed with you, but then I realized I don't know what you mean by "execution" here, though.
This statement "The more complicated a model is, the less well you can execute it" is fishy though. The typical problem in practice with complicated models is the data quality and quantity to support it, not the implementation or interpretation. I suppose here we also need to define "complexity" - I am using this to mean roughly number of parameters.
- jackcosgrove 9y agoI took "execution" here to mean "scaling up". In a trivial case, a model may fail to scale up if it's computationally too slow or too sensitive to noisy data. Sometimes these shortcomings cannot be tested in a laboratory environment with limited data sets.