Logistic Regression

What is logistic regression?

Logistic regression is a Machine Learning classification algorithm that is used to predict the probability of certain classes based on some dependent variables. In short, the logistic regression model computes a sum of the input feature (in most cases, there is a bias term), and calculates the logistic of the result.

The output of a logistic regression is always between (0, 1), which is suitable for a binary classification task. The higher the value, the higher the probability that the current sample is classified as class=1, and vice versa.

$$h_{\theta}(x) = \frac{1}{1+e^{-\theta x}}$$

As the formula above shows, $\theta$ is the parameter we want to learn or train or optimize and $x$ ...