AUC (Area Under the Curve) – The Performance-Based Model Selector for Pega Binary Prediction Models
The metrics for binary models is AUC, F-score for categorical models and RMSE for continuous models. The higher the AUC, the better a model is at predicting the outcome. ADM selects features based on their individual univariate performance against the outcome, measured as the area under the curve (AUC) of a ROC graph. By default, the univariate performance threshold is set to 0.52 AUC. Those statements are copied from the official Pega training documents of PCDS (Pega Certified Data Scientist) exam. AUC is treated as an important performance metrics to select the best Pega Prediction Model and to select theRead More
......Pega Certified Exam for Decisioning Consultant & Data Scientist (PCDC, PCDS)
Within two-month study (Oct and Nov, 2022), I passed the PCDC exam and the PCDS exam via self-learning from the official Pega Academy website. I got high scores (91 and 96 out of 100) for the two exams respectively. I would like to share the high levels of those exams. Hope it may help you on the journey. (I also passed the Pega Certified Senior System Architect (PCSSA) at Sept 2022.) 1. Here are the two score reports and certificates as evidences. ( to make you have confidence on this blog). 2. The learning schedules Normally, I read the mission documentsRead More
......Tax Incidence formulas in the view of producer and consumer
My daughter attends her first college class, Micro economy, at the summer of her junior year. So, it is time to go over some economy concepts that I learnt before to prepare questions from daughter. Get the textbook from Prof. Jeffrey M. Perloff – Microeconomics_ Theory and Applications with Calculus (Pearson, 4th) Of course, this textbook full of math formula is different than my daughter’s economy class. But I always prefer math formula than the description. When reading the tax incidence formula in the textbook, it is different than the formula mentioned in Harvard’s’ economy class lecture ppt, https://scholar.harvard.edu/files/stantcheva/files/lecture3.pdf. Of course,Read More
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