Overfitting and Underfitting in Machine Learning

Overfitting is caused by the size of the data We know that the more the data more the model will learn hence, we try to give better predictions

Overfitting in machine learning occurs when a statistical model fits or comes too close to its training data, introducing more bias and

overfitting In an overfitting scenario, models have learned the random fluctuations and noise from training datasets, resulting in the models handling noise

overfitting The common pattern for overfitting can be seen on learning curve plots, where model performance on the training dataset continues to improve (