As for tests ... in an ideal world we would have some. At least a test ensuring that (re-)training with landmark loss actually runs. Ensuring that it "does what we expect" is harder. Maybe a very simple case with, say pendigits and a leave-one-out class and simply verifying that ...
please pass a DimReduc object with the model stored to reduction.model.", call. = FALSE ) } # 模型 model <- Misc( object = reduction.model, slot = "model" ) # 如果长度为0,报错 if (length(x = model) == 0) { stop( "The provided reduction.model does not have a model stored...
The algorithm does not assign lower density points to any cluster, marking them as Noise. In this work, we referred to them as Not Clusterable (NC) points. Moreover, the algorithm requires two main hyperparameters to be defined. The first hyperparameter, Min Cluster Size (MCS), is the mi...