When training a logistic regression model, there are many optimization algorithms that can be used, such as stochastic gradient descent (SGD), iterated Newton-Raphson, Nelder-Mead and L-BFGS. This ...

But there is also some empirical work comparing various algorithms across many datasets and drawing some conclusions, what types of problems tend to do better with trees vs logistic regression.

Logistic regression can be applied in customer service, when you examine historical data on purchasing behaviour to personalise offerings. The afterword We’ve touched upon three common models of ...