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import numpy
from matplotlib import pyplot
labels = [
"unigrams, frequency",
"unigrams, frequency, +Position",
"unigrams, presence",
"unigrams, presence, +Position",
"bigrams, frequency",
"bigrams, frequency, +Position",
"bigrams, presence",
"bigrams, presence, +Position",
"delta_tfidf",
"unigrams, presence, +POS",
"bigrams, presence, +POS"
]
labels2 = [
"unigrams, frequency",
"unigrams, frequency, +Position",
"unigrams, presence",
"unigrams, presence, +Position",
"bigrams, frequency",
"bigrams, frequency, +Position",
"bigrams, presence",
"bigrams, presence, +Position",
"delta_tfidf",
"unigrams, presence, +POS",
"bigrams, presence, +POS"
]
bottoms = numpy.arange(len(labels))
widths = [0.826002649356, 0.784479089868, 0.842490694287, 0.821997146847, 0.807497617378, 0.777000053946, 0.820491149832, 0.795509581438, 0.981992471513, 0.836989684295, 0.818997140853]
widths2 = [0.824624634419, 0.808376475678, 0.832750728912, 0.815374570779, 0.797876474366, 0.771876439875, 0.799001849413, 0.768376127015, 0.929999178955, 0.813999695576, 0.792252879562]
height = 0.3
pyplot.barh(bottoms, widths, height, color="#FF0000")
pyplot.barh(bottoms-height, widths2, height, color="#00FF00")
pyplot.legend(["Movies", "Amazon"], loc=4) # bottom right
pyplot.yticks(bottoms, labels)
pyplot.xlim(0.5, 1.0)
#pyplot.ylim(tops[0]-2*height, bottoms[-1]+3*height)
pyplot.show()
"""
# TODO: Use POS tags on Amazon dataset.
gram_length: 1, use_presence: False, use_amazon: False, use_pos_tags: True, use_adj_only: False, use_position: False 0.822003140865
gram_length: 1, use_presence: False, use_amazon: False, use_pos_tags: True, use_adj_only: False, use_position: True 0.781988575402
gram_length: 1, use_presence: False, use_amazon: False, use_pos_tags: True, use_adj_only: True, use_position:False 0.77899606193
gram_length: 1, use_presence: False, use_amazon: False, use_pos_tags: True, use_adj_only: True, use_position:True 0.762512512513
gram_length: 1, use_presence: True, use_amazon: False, use_pos_tags: True, use_adj_only: False, use_position:False 0.836989684295
gram_length: 1, use_presence: True, use_amazon: False, use_pos_tags: True, use_adj_only: False, use_position:True 0.814993136849
gram_length: 1, use_presence: True, use_amazon: False, use_pos_tags: True, use_adj_only: True, use_position: False 0.769011526497
gram_length: 1, use_presence: True, use_amazon: False, use_pos_tags: True, use_adj_only: True, use_position: True 0.749997002991
gram_length: 2, use_presence: False, use_amazon: False, use_pos_tags: True, use_adj_only: False, use_position: False 0.800000599402
gram_length: 2, use_presence: False, use_amazon: False, use_pos_tags: True, use_adj_only: False, use_position: True 0.762980045914
gram_length: 2, use_presence: False, use_amazon: False, use_pos_tags: True, use_adj_only: True, use_position:False 0.707506908106
gram_length: 2, use_presence: False, use_amazon: False, use_pos_tags: True, use_adj_only: True, use_position:True 0.669494344644
gram_length: 2, use_presence: True, use_amazon: False, use_pos_tags: True, use_adj_only: False, use_position:False 0.818997140853
gram_length: 2, use_presence: True, use_amazon: False, use_pos_tags: True, use_adj_only: False, use_position:True 0.78900607194
gram_length: 2, use_presence: True, use_amazon: False, use_pos_tags: True, use_adj_only: True, use_position: False 0.714507921095
gram_length: 2, use_presence: True, use_amazon: False, use_pos_tags: True, use_adj_only: True, use_position: True 0.668990847135
"""
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