2 docs tagged with "#data/data-cleaning"

As you can see from the above image, confident learning is about estimating the likelyhood of the data being labeled correctly based upon the confidence of the model. If the model confidence is above the threshold confidence (The Tj parameter, tdog, tfox tcow) and if the confidence of the model prediction is higher than the threshold but the label is different, then we predict a wrong label

Data Cleaning is the process of turning the data you have into data that is usable. It is, for the lack of a better term, the fight against entropy in the data domain.