About this document
Understanding Overfitting and Underfitting by swethaa1859 is a document available to read on EtoBox.
Overfitting and underfitting are issues in machine learning where overfitting leads to high accuracy on training data but poor performance on unseen data, while underfitting results in poor performance on both training and test data. Overfitting is caused by overly complex models and can be mitigated through simpler models and regularization, whereas underfitting arises from overly simplistic models and can be addressed by increasing model complexity and training duration. Both concepts are related to the b
- Author
- swethaa1859
- Language
- EN