Database Reference
In-Depth Information
Training classification models
Now that we have extracted some basic features from our dataset and created our input
RDD, we are ready to train a number of models. To compare the performance and use of
different models, we will train a model using logistic regression, SVM, naïve Bayes, and a
decision tree. You will notice that training each model looks nearly identical, although each
has its own specific model parameters that can be set. MLlib sets sensible defaults in most
cases, but in practice, the best parameter setting should be selected using evaluation tech-
niques, which we will cover later in this chapter.
