Melanie Carey has worked at SAS for over 18 years. She started out as a consultant assisting customers on their Activity Based Costing models and Strategic Performance initiatives. She then worked on cutting edge initiatives like Social Media Analytics and Launch Revenue Optimization in the Emerging Technologies group. She has created numerous demo's for the field and has taken the lead for the Visual Analytics Interactive Reports available on sas.com. Melanie currently works within Cloud and Information Services as the technical lead for SAS product trials.
Remember back to your early school days, singing with all your classmates “If you’re happy and you know it clap your hands!” and then we’d all clap our hands. Being happy back then was so simple. Today, it’s hard to get away from all the negative headlines of 2020! It’s
What is automated prediction? Automated prediction, in less than a minute, runs several analytic models (such as decision trees, gradient boosting, and logistic and linear regression) on a specific variable of your choice. Most of the remaining variables in your dataset are automatically analyzed as factors that might influence your specified variable. They are called underlying factors. SAS then chooses the one model (champion model) that most accurately predicts your target variable. The model prediction and the underlying factors are then displayed. You can adjust the values of the underlying factors to determine how the model prediction changes with each adjustment.
How have healthcare providers and governmental agencies predicted the fast-changing, potentially exponential increase in the need for medical services and equipment through the various stages of the COVID-19 pandemic? Mathematical techniques that attempt to model and understand the likely spread of the disease have been instrumental. The SEIR model is
