k-fold cross-validation
Selecting features on pure noise before the split turns a chance-level problem into 90 percent accuracy. Inside a pipeline it reads 0.53.
Selecting features on pure noise before the split turns a chance-level problem into 90 percent accuracy. Inside a pipeline it reads 0.53.