Introduction
Do you ever wonder what happens when you train a machine learning model on really bad data? In this article, we show the effect of bad data on a machine learning model. Specifically, we take a good data set conducive towards modeling and distort the data in two different ways. First, we randomly distort the labels and train models using this randomly distorted label field. Second, we distort the labels in a biased way and then again train models using this distorted label field. These two types of distortion will allow us to see how different types of bad data can affect a model.
