Document classification: tf-idf prior to or after feature filtering?
As you've described it, Step 4 is where you want to use TF-IDF. Essentially, TD-IDF will count each term in each document, and assign a score given the relative frequency across the collection of documents.

There's one big step missing from your process, however: annotating a training set. Before you train your classifier, you'll need to manually annotate a sample of your data with the labels you want to be able to apply automatically using the classifier.

To make all of this easier, you might want to consider using the Stanford Classifier. It will perform the feature extraction and build the classifier model (supporting several different machine learning algorithms), but you'll still need to annotate the training data by hand.