If the outcome variable is a continuous variable, linear regression is more suitable. The key difference between the two is that logistic regression uses a statistical function (the logistic or ...

James McCaffrey of Microsoft Research demonstrates applying the L-BFGS optimization algorithm to the ML logistic regression ... The sigmoid() function applies logistic sigmoid to the sum. The forward( ...

Logistic regression, therefore, makes a prediction about two possible scenarios: For example ... Logistic regression employs a logistic function with a sigmoid (S-shaped) curve to map linear ...

In this example, because the p2 pseudo-probability is the largest, the prediction is class 2. Although it's not obvious, there is a very close but complex mathematical relationship between the ...