These visualisations are great but misleading regarding the performance of these classifiers. In practice you don't have a lot of data in a small number of dime

These visualisations are great but misleading regarding the performance of these classifiers. In practice you don't have a lot of data in a small number of dimensions (2 in this case). You have a little bit of data in zillions of dimensions. Think of classifying a 100x100 pixel image: that's 3x100x100=30000 dimensional data. You may not even have one training sample per class per dimension. Generalizing from comparatively little data to a very high dimensional space is the true difficulty of machine learning. Unfortunately you can't easily visualize that.