Overfitting

In both machine learning and statistics, overfitting occurs when the model fits the data too well or simply put, when the model is too complex. Overfitting model learns the detail and noise in the training data to such an extent that it negatively impacts the performance of the model on new data/test data.

Overfitting problem can be solved by decreasing the number of features/inputs or by increasing the number of training examples to make the machine learning algorithms more generalized. The more common way of solving overfitting problem is by regularization.