def main(self, movies):
vectorize = vectorization.vector()
classify_movies = {}
print "#################################"
print "Movies to classify"
for movie in movies:
classify_movies[movie['imdb_id']] = movie
print "Title: %s" % movie['title']
print "#################################"
classify_movies_vectors = vectorize.vectorize(classify_movies.itervalues(), self.classified, 'classified')
# Execute classifier algorithm
errorsum = 0
count = 0
for movie in classify_movies_vectors:
oldrating = classify_movies_vectors[movie]['rating']
classify_movies_vectors[movie]['rating'] = self.k.avgrating
actor_rating = self.k.classify(classify_movies_vectors[movie], 'actors')
director_rating = self.k.classify(classify_movies_vectors[movie], 'directors')
writer_rating = self.k.classify(classify_movies_vectors[movie], 'writers')
plot_rating = self.k.classify(classify_movies_vectors[movie], 'plot')
genre_rating = self.k.classify(classify_movies_vectors[movie], 'genres')
count = count+1
avg = (actor_rating*.14) + (director_rating*.2) + (plot_rating*.19) + (genre_rating*.28) + (writer_rating*.13)
classify_movies_vectors[movie]['rating'] = avg
classify_movies[movie]['rating'] = avg
self.classified.insert(classify_movies[movie])
error = math.fabs((oldrating - avg)/oldrating)
if error < 90:
errorsum = errorsum + error
title = classify_movies_vectors[movie]['title']
"""
print count
print
print "Title: %s" % title
print "Actor rating: %f" % (actor_rating)
print "Director rating: %f" % (director_rating)
print "Writer rating: %f" % (writer_rating)
print "Genre rating: %f" % (genre_rating)
print "Plot rating: %f" % (plot_rating)
print "----------------------"
print "Final Rating: %f" %(avg)
print "Actual Rating: %f" %(oldrating)
print "Error: %f" %(error*100)
"""
self.classified.create_index('imdb_id')
"""
def train_classifier(self, training_movies):
vectorize = vectorization.vector()
# Vectorize movie data and traing classifier
training_movies = vectorize.vectorize(training_movies, self.training, 'training')
self.training.create_index('imdb_id')
print "Training with %d movies" % len(training_movies)
self.k.train(training_movies)
def setUp(self):
self.vector = vectorization.vector()
self.training = self.vector.vectorize(iter(training_movies))
self.knn = knn.knn()
def setUp(self):
self.vector = vectorization.vector()
self.movie_vectors = self.vector.vectorize(iter(training_movies))
