Your Prediction Gets As Good As Your Data

In the past, I have often seen that software engineers and data scientists assume that they can keep increasing their prediction accuracy by improving their machine learning algorithm. Here, I want to approach the classification problem from a different angle where I suggest data scientists analyze the distribution of their data to measure the information level in their data. This approach gives us an upper bound for how far we can improve the accuracy of a predictive algorithm and make sure our optimization efforts are not wasted. In the past, I have often seen that software e