ELI5: Explain Like I'm 5

Learning vector quantization

Learning vector quantization is a way of taking a lot of data and breaking it down into smaller parts so that it can be easier to understand. Each smaller part is called a 'vector', and each vector can be used to represent a piece of information. With learning vector quantization, computers can figure out the best way to organize these vectors so that they can make sense of the data quickly and accurately. Think of it like putting together a jigsaw puzzle: the pieces of the puzzle are like 'vectors', and the jigsaw puzzle is the data. The computer is able to figure out quickly where each piece of the puzzle should go, to make a beautiful picture!