Brief overview of objectives, methods, key findings, and recommendations.
A risk analyst uses on 1 million customer service tickets. By extracting latent topics, they discover that a specific phrase ("API timeout") correlates with high churn risk. They export the topic probabilities back into the data table and run a Logistic Regression (Pro’s Generalized Regression) with elastic net regularization to build a high-accuracy churn prediction model. jmp 17 pro
for cleaning and modeling "curve" data, such as IR, Mass Spec, and NMR. Generalized Linear Mixed Models (GLMM) Brief overview of objectives, methods, key findings, and