Machine Learning for OpenCV 4 - Second Edition

Taking a short detour through probability theory

In order to appreciate Bayes' theorem, we need to get a hold of the following technical terms:

• Random variable: This is a variable whose value depends on chance. A good example is the act of flipping a coin, which might turn up heads or tails. If a random variable can take on only a limited number of values, we call it discrete (such as a coin flip or a dice roll); otherwise, we call it a continuous random variable (such as the temperature on a given day). Random variables are often typeset as capital letters.
• Probability: This is a measure of how likely it is for an event to occur. We denote the probability of an event, e, happening as p(e), which must be a number between 0 and 1 (or between ...