https://github.com/gtraines/logistic-regression-classification

Logistic regression is a type of machine learning approach to the classification of noisy data. Whereas linear classification requires data to be linearly separable in order to find the decision hyperplane, logistic regression allows for the expression of uncertainty by providing a probability that a given sample should be placed into one class or the other.

Logistic regression calculates the probability by running the vector of of inputs and weights through a logistic or “sigmoid” function which Continue reading Logistic Regression with Gradient Descent – Some Thoughts and Lessons →

## always choosing the local optimum