Regression

Definitions

1. Regression is a supervised learning method for estimating numeric outputs from input features. It is commonly used for prediction pipelines and baseline modeling tasks, where teams need predictable behavior under real workloads rather than toy examples. Practitioners pay attention to feature quality, regularization, and error metrics, because those factors usually determine whether the approach improves quality, latency, reliability, or operating cost in production.

   In plain English: Regression is an AI concept teams use to train models, guide predictions, or make model behavior more reliable and easier to control in practice.

   Example: "We evaluated Regression in the new model pipeline because the baseline was plateauing; once it was wired into training and evaluation, quality improved enough to justify rolling it into the next release."

Related Terms

• Lemmatization
• Linear Layer
• Linear Probe
• Linear Regression
• Llama
• Logistic Regression
• Logit
• Long Short-Term Memory