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the data for your supervised learning problem comprises input X and output labels Y what have you going through your data you find that some of these upper labels Y are incorrect the up data which is incorrectly labeled is it worth your while to go in to fix up some of these labels letamp;#39;s take a look in the classification problem y equals 1 for cats and 0 for non cats so letamp;#39;s say youamp;#39;re looking through some data and thatamp;#39;s a cat that smelly cat does the cat thereamp;#39;s a cat thatamp;#39;s not a cat thatamp;#39;s a cat you know wait thatamp;#39;s actually not a cat so this is an example with an incorrect label so Iamp;#39;ve used the term mislabeled examples to refer to if your learning algorithm Iamp;#39;ll put the wrong value of Y but Iamp;#39;m going to say incorrectly labeled examples when to refer to if in the data set you have in a training set or the death set or the test set the label for Y whenever a human label assigned to this piece o
