A Gentle Introduction to Concept Drift in Machine Learning - Machine Learning Mastery

Data can change over time. This can result in poor and degrading predictive performance in predictive models that assume a static relationship between input and output variables. This problem of the changing underlying relationships in the data is called concept drift in the field of machine learning. In this post, you will discover the problem of concept drift and ways to you may be able to address it in your own predictive modeling problems. A Gentle Introduction to Concept Drift in Machine Learning Photo by Joe Cleere, some rights reserved. Predictive modeling is the problem of learning a model from historical data and using the model to make predictions on new data where we do not know the answer.