I'm writing code for a neural network, and I'm wondering whether I should do it or not. I'm actually somewhat worried that even using double might not wield good results and that I might have to migrate my code to a more efficient language, like c++. I've read in a question here that BigDecimal is 1000 times slower than double? That's a lot.
On the other hand, I'm going to be working a lot with decimal numbers and having it be more precise would always be good. I can't really tell if the precision could cause problems to it, either. I don't think any of the implementations I've seen around do it either, so I'm probably not gonna do it. Although sometimes the network doesn't behave as it should; whether that's a precision error or a problem with its logic, I'm not sure.
But I'm wondering, do you guys only use BigDecimal when dealing with money? Any thoughts about this?
Using Java's double data type for weights in a neural network seems very appropriate. It is a good choice for engineering and scientific applications.
Neural networks are inherently approximate. The precision of BigDecimal would be meaningless in this application, performance impact aside. Reserve BigDecimal primarily for financial applications.