You Evaluate the algorithm with most of the data

man in black coat sitting at the table

You start separating out the data into various train-test chunks and it all works just the same. When you run the numbers on how well it fits, you get some log likelihood metric, it looks good, but you’re still not sure… What do you do?

Try Another Algorithm—I don’t trust this unsupervised stuff

Try more data—What’s the worst that can happen, the algorithm should sort it all out

Try less Data—There’s gotta be some research on the best way to pick your feature space

Good enough for Government Work, lets see how it turns out

Published by B McGraw

B McGraw has lived a long and successful professional life as a software developer and researcher. After completing his BS in spaghetti coding at the department of the dark arts at Cranberry Lemon in 2005 he wasted no time in getting a masters in debugging by print statement in 2008 and obtaining his PhD with research in screwing up repos on Github in 2014. That's when he could finally get paid. In 2018 B McGraw finally made the big step of defaulting on his student loans and began advancing his career by adding his name on other people's research papers after finding one grammatical mistake in the Peer Review process.

Leave a Reply

%d bloggers like this: