Save Naive Bayes Trained Classifier in NLTK

classification, machine-learning, naivebayes, nltk, python

Solution

To save:

import pickle
f = open('my_classifier.pickle', 'wb')
pickle.dump(classifier, f)
f.close()

To load later:

import pickle
f = open('my_classifier.pickle', 'rb')
classifier = pickle.load(f)
f.close()

Problem

I'm slightly confused in regard to how I save a trained classifier. As in, re-training a classifier each time I want to use it is obviously really bad and slow, how do I save it and the load it again when I need it? Code is below, thanks in advance for your help. I'm using Python with NLTK Naive Bayes Classifier. ``` classifier = nltk.NaiveBayesClassifier.train(training_set) # look inside the classifier train method in the source code of the NLTK library def train(labeled_featuresets, estimator=nltk.probability.ELEProbDist): # Create the P(label) distribution label_probdist = estimator(label_freqdist) # Create the P(fval|label, fname) distribution feature_probdist = {} return NaiveBayesClassifier(label_probdist, feature_probdist) ```

Original source