-
Proving the Tradeoff. A New Way to Think About Precision and Recall.
Fifth in a Series: Mastering data quality for safe and scalable AI Saibal Banerjee, PhD and Steven Atneosen, JD Introduction Every AI practitioner knows the uneasy balance: boosting precision usually costs recall, and maximizing recall often tanks precision. Yet in high-stakes workflows – healthcare diagnostics, fraud detection, border security, or financial approvals – “intuition” about…
-
Measure twice, cut once. Weighted metrics matter.
Fourth in a Series: Mastering data quality for safe and scalable AI Saibal Banerjee, PhD and Steven Atneosen, JD Introduction AI practitioners often struggle with assessing the performance of multi-class classification models. When your model has to recognize multiple categories, especially if the populations of these categories are imbalanced – i.e., they vary widely –…
-
If it walks like a duck, talks like a duck, it’s a pig… The Confusion Matrix is a simple tool for model performance
Third in a Series: Mastering data quality for safe and scalable AI Saibal Banerjee, PhD and Steven Atneosen, JD Introduction If there’s one tool every data scientist should master, it’s the confusion matrix. Despite its simplicity, it offers unparalleled insight into model performance, including class-wise behaviors, average trends, systemic biases, and types of errors. If…
-
CASE STUDY: Precision Health/Insuretech
Data savvy precision health reinsurance analytics company leverages tomtA.ai to access all sensitive health data at scale to vastly increase predictive ability value to self-insured employers to determine cost of healthcare for their people Mission: To aid self-insured employers to cut costs and preserve vital class leading healthcare benefits for employees. Problem: No safe access…
-
CASE STUDY: Fintech Collaborator
Traditional, Legacy Credit Card Company Leverages tomtA.ai to Take On Disruptive Competitors Mission: To aid self-insured employers to cut costs and preserve vital class leading healthcare benefits for employees. Problem: No safe access to vast data at an individual level to properly assess risk Problem of Disruptive InnovationTraditional credit card companies face disruption from smart…
