search for: pass_selection

...= 1) passing_Devices <- measurements[selection,1:138] failing_Devices <- measurements[-selection,1:138] #Number of passing/failing devices num_Passing_Devices <- dim(passing_Devices)[1] num_Failing_Devices <- dim(failing_Devices)[1] # Use probability vectors to make vectors of indices pass_Selection <- which (runif(num_Passing_Devices) > 0.5) fail_Selection <- which (runif(num_Failing_Devices) > 0.5) # ... which are then used to establish training and validation data sets with each set containing # ~50% of "good" and ~50% of "bad" data points training_Set &...