leave-one-out error

  1. M

    Leave-one-out error strictly decreasing when number of parameters is increased, when it should not be?

    People may or may not be able to help intuitively shed light on my problem. Maybe I haven't considered some aspects. I'm running a non-parametric (kernel) regularized least squares estimation on some binary training data to then predict probabilistic values for the non-training data. I have 9...