I'm working with a dataset containing crimes data from Chicago. There's a lot of geographical data, and I'm looking for advice on pre-processing.
We have qualitative variables represented by integers, the blocks for example : 2 blocks with a close number aren't necessarily close to each other.
- Will the algorithms learn based on an order that doesn't mean anything ? If so, which machine learning algorithms can/can't I use ?
- Is it better to insert dummy variables (one column per value) ? But what if there is a lot of values (more that 30 000 here) ?