Hands-On Machine Learning for Algorithmic Trading

Maximum likelihood estimation

The coefficient vector must be estimated using the available training data. Although we could use (non-linear) least squares to fit the logistic regression model, the more general method of maximum likelihood is preferred, since it has better statistical properties. As we have just discussed, the basic intuition behind using maximum likelihood to fit a logistic regression model is to seek estimates for such that the predicted probability corresponds as closely as possible to the actual outcome. In other words, ...