Model Building is Hard. Don’t Lose Hope If You Fail.

Here we are at the last project of the term for the first semester of my MSBA degree at Wake Forest. And now is a great time for a failed model building experience. The assignment was to build a logistic regression model (or random forest/gradient boosting if one wanted to give it a try) to … Continue reading Model Building is Hard. Don’t Lose Hope If You Fail.

Don’t Crash Your Laptop While Running Random Forest in R

Or more specifically, be careful to manage your machine's resources if you decide to run parallel jobs using RStudio. The latest version of RStudio makes it very easy to set up multiple jobs at the same time. All you need to do is put the code you'd like to run in a separate script, click … Continue reading Don’t Crash Your Laptop While Running Random Forest in R

Linear Regression With SAS

It probably seems like I complain a lot about SAS (I have), so today I'll write about something that I've learned from SAS that is really useful and a huge time saver when creating a generalized linear regression model. Proc GLMSelect makes the process of variable selection and transformation really easy. Specifically the Effect statement … Continue reading Linear Regression With SAS

Proc Fastclus Is Going to be Useful

This week in learning SAS we began working with Proc Fastlclus - a procedure to group data together by two or more variables. This is particularly useful for data that has little linear relationship. Once you've identified clusters it helps to find similar characteristics among the clusters to aid in predicting outcomes for other observations … Continue reading Proc Fastclus Is Going to be Useful