Logistic regression is a classification algorithm used to predict a binary outcome (e.g. 0 or 1, yes or no, etc.). Here is an example of how you could implement logistic regression in C++
In this code, the predict function takes a vector of input features, x, and a vector of model weights, w, and returns the predicted binary outcome using the logistic regression model. The gradient function computes the gradient of the log loss with respect to the model weights, which is used in the gradient_descent function to learn the model