Overfitting and Underfitting in Machine Learning

In this article, we are going to indulge in two of the most discussed about and important concepts in machine learning which is related to the performance of a model. How do we know a model is performing better? Which model should we choose? For eg: I applied linear regression and decision tree algorithm on the train dataset of a classification problem. From above table, we can see that delta value from decision tree (5%) delta value from linear regression (20%), hence Decision would be perform best in this scenario. Note: Lower the delta value, higher the performance of the model.