Last week in our Analytics Journey, we worked on variable selection in the Modeling stage of the CRISP-DM method. Having built a model, it’s once again time to see how it did with the Evaluation stage. One of the most important parts of evaluating a model comes in properly constructing a training and testing set for evaluation.
Jason is a Junior Data Scientist at Ruths.ai with a Master’s degree in Predictive Analytics and Data Science from Northwestern University. He has experience with a multitude of machine learning techniques such as Random Forest, Neural Nets, and Hidden Markov Models. With a previous Master’s in Creative Writing, Jason is a fervent believer in the Oxford comma.