[bunderbunder]

Simple regression has a lot going for it beyond simply being a simpler model. For example, it produces models that are easy to interpret. That is an enormous advantage if you're looking to use data science to help drive strategic decisionmaking.

My personal suspicion is, in a market full of people who are using ever more sophisticated algorithms to ratchet up their customer conversion classifiers' F1 scores by .001 per iteration, the leader will be the company who's decided to steer clear of that quagmire and spend their time and money on identifying new business opportunities instead.

[nightski]

I think calling linear regression simple is misleading. While the algorithm is simple, interpreting the results and not falling into one of the many traps is quite difficult!

[Noseshine]

His comment was relative to ML, not an absolute.

[nightski]

Mine was also. I am just pointing out that even with a simple algorithm like linear regression you can run into all kind of issues and it's not always obvious. Sometimes a slightly more complex method is easier to get right in the long run. It depends on many factors.