concept curve in category machine learning

This is an excerpt from Manning's book Machine Learning with R, the tidyverse, and mlr. Login to get full access to this book.

Figure 4.3. Modeling the data with the logistic function. The S-shaped curve represents the logistic function fitted to the data. The center of the curve passes through the mean of copper content and maps it between 0 and 1.

This is an excerpt from Manning's book Machine Learning for Business: Using Amazon SageMaker and Jupyter. Login to get full access to this book.

XGBoost is good at learning. But what does it mean to learn? It simply means that the model gets punished less and rewarded more. And how does the machine learning model know whether it should be punished or rewarded? The area under the curve (AUC) is a metric that is commonly used in machine learning as the basis for rewarding or punishing the function. The curve is the “When the function gets a greater area under the curve, it is rewarded” guideline. When the function gets a reduced AUC, it is punished.

The area under the curve (AUC) showing true and false positive values