In machine learning, what we suppose to do if we see a redundant instances and a conflict instances? for example, in the breast cancer data set I noticed
the following redundant instance :(perhaps due to discretizing)
40-49,premeno,25-29,0-2,no,2,right,left_low,no,recurrence-events
40-49,premeno,25-29,0-2,no,2,right,left_low,no,recurrence-events
and the following conflict (diffrent outcomes for the same input data)
30-39,premeno,0-4,0-2,no,2,right,central,no,recurrence-events
30-39,premeno,0-4,0-2,no,2,right,central,no,no-recurrence-events
30-39,premeno,30-34,0-2,no,2,left,left_up,no,no-recurrence-events
30-39,premeno,30-34,0-2,no,2,left,left_up,no,recurrence-events
40-49,premeno,20-24,0-2,no,2,left,left_low,no,no-recurrence-events
40-49,premeno,20-24,0-2,no,2,left,left_low,no,recurrence-events
40-49,premeno,25-29,0-2,no,2,right,left_low,no,recurrence-events
40-49,premeno,25-29,0-2,no,2,right,left_low,no,no-recurrence-events
40-49,premeno,30-34,0-2,no,3,right,right_up,no,no-recurrence-events
40-49,premeno,30-34,0-2,no,3,right,right_up,no,recurrence-events
50-59,premeno,25-29,0-2,no,1,right,left_up,no,recurrence-events
50-59,premeno,25-29,0-2,no,1,right,left_up,no,no-recurrence-events
Should I discard them? to determine the accuracy? or change the outcome to be something like conflict?