April 2018
Intermediate to advanced
408 pages
10h 42m
English
A number of decision-making problems require that we find a close enough match. We might not be able to use a simple equality test. Instead, we have to use a distance metric and locate items with the shortest distance to our target. For text, we might use the Levenshtein distance; this shows how many changes are required to get from a given block of text to our target.
We'll use a slightly simpler example. This will involve very simple math. However, even though it's simple, it doesn't work out well if we approach it naively.
When doing color matching, we won't have a simple equality test. We're rarely able to check for the exact equality of pixel colors. We're often forced to define a minimal distance function to determine ...