Validating an algorithm
Validating an algorithm confirms that it is actually providing a mathematical solution to the problem we are trying to solve. A validation process should check the results for as many possible values and types of input values as possible.
Exact, approximate, and randomized algorithms
Validating an algorithm also depends on the type of the algorithm as the testing techniques are different. Let’s first differentiate between deterministic and randomized algorithms.
For deterministic algorithms, a particular input always generates exactly the same output. But for certain classes of algorithms, a sequence of random numbers is also taken as input, which makes the output different each time the algorithm is run. The k-means clustering algorithm, which is detailed in Chapter 6, Unsupervised Machine Learning Algorithms, is an example of such an algorithm:
Figure 1.4: Deterministic and Randomized Algorithms
Algorithms can also be divided...
