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It bothers me that these data sets are very low dimensional, without noise and pretty-picture-like. This pretty much excludes any interesting data to try to lea
by alextp 17y ago
It bothers me that these data sets are very low dimensional, without noise and pretty-picture-like. This pretty much excludes any interesting data to try to learn (after all one could easily manually code a classifier for most os these "concepts" that performs 100%)
- gjm11 17y agoRight. This also biases the test toward certain kinds of algorithm. The implicit requirement that the thing being learned should be something you can see (and check) by looking at pictures like these pretty much guarantees that simple "proximity-based" approaches will do well. So it's no surprise that we see nearest-neighbours and radial basis functions looking good in these tests.