The rather colorful term decapitate is borrowed from the data miner Dorian Pyle. Everyone 30 days late on their mortgage receives a late letter, but receiving a late letter is not a good predictor of lateness because their lateness caused the letter, not the other way around. When this occurs we have accidentally allowed information into the model that could not possibly be known at the time of the prediction. Perfect predictors earn their name by being correct 100 percent of the time, usually indicating circular logic and not a prediction of value. In this recipe, we will identify perfect or near perfect predictors in order to insure that they do not contaminate our model. (For more resources related to this topic, see here.) Using the Feature Selection node creatively to remove or decapitate perfect predictors
0 Comments
Leave a Reply. |
Details
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |