Another important distinction relates to the bias/variance tradeoff -- some machine learning methods are are capable of recognizing more complex patterns, but the tradeoff is that these methods can overfit and generalize poorly if there's noise in the training data -- especially if there's not much training data available.
Another important distinction relates to the bias/variance tradeoff -- some machine learning methods
areare capable of recognizing more complex patterns, but the tradeoff is that these methods can overfit and generalize poorly if there's noise in the training data -- especially if there's not much training data available.