Optimizing Code by Not Being Lazy

A lot has happened in the last week. The most academic thing would be creating graphs of R2 as Providers Increases. The idea was to see when our model began to overfit the data and give us diminishing returns. Instead of continuing to give us a better model, at a certain number of providers, adding more providers will not give us a better prediction of death data. This is helpful for the CDC, because they can see how many providers make a good network.

What my professor asked me to do was to compile these graphs for each of the networks. The problem was that the program took days to run. No, I'm not exaggerating. It literally took days to run. Then, one night, while waiting for my program to finish running, I had a flash of inspiration. I could optimize my code. So I did. Originally, I had built models using a variable number of providers for each one of the 133 cities, but I was only using the models for New York.

That one simple change ended up making the code run hundreds of times faster. It took an hour to code and debug though, A whole hour! To be fair though, it saved me at least ten hours in the long run.

An example of a graph