Randomness in Artificial Intelligence & Machine Learning

Question

This question came to my mind while working on 2 projects in AI and ML. What If I\'m building a model (e.g. Classification Neural Network,K-NN, .. etc) and this model uses s

Answer 1

Stochastic techniques are typically used to search very large solution spaces where exhaustive search is not feasible. So it's almost inevitable that you will be trying to iterate over a large number of sample points with as even a distribution as possible. As mentioned elsewhere, basic statistical techniques will help you determine when your sample is big enough to be representative of the space as a whole.

To test accuracy, it is a good idea to set aside a portion of your input patterns and avoid training against those patterns (assuming you are learning from a data set). Then you can use the set to test whether your algorithm is learning the underlying pattern correctly, or whether it's simply memorizing the examples.

Another thing to think about is the randomness of your random number generator. Standard random number generators (such as rand from ) may not make the grade in many cases so look around for a more robust algorithm.