Archives for underfitting
Whenever a data scientist works to predict or classify a problem, they first detect accuracy by using the trained model to the train set and then to the test set. If the accuracy is satisfactory, i.e., both the training and testing accuracy are good, then a particular model is considered for further development. But sometimes,…
The post Understanding Overfitting and Underfitting for Data Science appeared first on Analytics India Magazine.
A machine learning model is only as good as the data it’s trained on. In other words, the poor performance of a model is mainly due to overfitting and underfitting. Overfitting happens when the model is modelled ‘too well’ on the training data. Underfitting refers to a model that can neither model the training data…
The post Why Is Overfitting So Demonized? appeared first on Analytics India Magazine.