Underfitting: A statistical model or a machine learning algorithm is said to have underfitting when it cannot capture the underlying trend of the data. (It’s just like trying to fit undersized pants!) Underfitting destroys the accuracy of our machine learning model. Its occurrence simply means that our model or the algorithm does not fit the data well enough. It usually happens when we have less data to build an accurate model and also when we try to build a linear model with a non-linear dat
Overfitting vs. Underfitting: What Is the Difference?
Overfitting vs. Underfitting: What Is the Difference?
Understanding Overfitting and Underfitting for Data Science
Do you know overfitting and underfitting?
Overfitting and Underfitting in Machine Learning Algorithms
Overfitting and Underfitting with a real-life example - Shiksha Online
Ultimate Guidebook for Regularization Techniques in Deep Learning.
Overfitting and Underfitting in Machine Learning
Underfitting and Overfitting in Machine Learning
Overfitting and underfitting in machine learning
