Logistic regression is preferrable over a simpler statistical test such as chi-squared test or Fisher’s exact test as it can incorporate more than one explanatory variable and deals with possible ...

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 ...

A variable undergoing logistic growth initially grows exponentially. After some time, the rate of growth decreases and the function levels off, forming a sigmoid, or s-shaped curve. For example ...