 Is the curse of dimensionality the same as overfitting? In many fields of mathematics, as we increase the number of dimensions of data, the sense of relative distances vanishes. So in a very high dimensional space, distance AB and AC becomes indistinguishable, which can cause overfitting, as any small changes in this data can cause different model behavior. However, overfitting itself can be caused by other factors outside high dimensional space. And so the curse of dimensionality is only one cause of overfitting, but overfitting itself can be caused outside of high dimensional spaces.