feature_type='chars',
ngram_range=4,
sample_authors=False,
sample_features=False,
n_features=10000,
n_dev_pairs=1000000000000,
vector_space_model='std',
balanced_pairs=False)
verifier.vectorize(verif_dataset)
dev_results = verifier.fit()
dev_f, dev_p, dev_r, dev_t = evaluate(dev_results)
max_f = np.nanmax(dev_f)
print('\t\t + F1 (pairwise):', max_f)
print('getting distance table')
df = verifier.get_distance_table(verifier.dev_dists, verifier.dev_pairs, 'dev')
df.to_csv('outputs/dm_no_sampl.csv')
print('saved dist table!')
df = pd.read_csv('outputs/dm_no_sampl.csv')
df = df.set_index('id')
print('loaded dist table!')
top_scores = 0
if top_scores:
scores = []
for author1 in df.index:
for author2 in df.columns:
if author1.split('_', 1)[0] != author2.split('_', 1)[0]:
sc = df[author1][author2]
if sc > 0:
verifier = Verification(random_state=1000,
metric=dm,
n_features=10000,
n_dev_pairs=0,
n_test_pairs=99999999,
vector_space_model=vsm,
balanced_pairs=False,
control_pairs=False)
logging.info("Starting verification [train / test]")
verifier.vectorize(X_dev, X_test)
train_results, test_results = verifier.predict(filter_imposters=False)
logging.info("Computing results")
test_df = verifier.get_distance_table(verifier.test_dists, verifier.test_pairs,
"test")
test_df.to_csv("../outputs/caesar_test.csv")
test_df = pd.read_csv("../outputs/caesar_test.csv")
test_df = test_df.set_index("id")
test_df = test_df.applymap(lambda x: int(x * 1000)).corr()
# heatmap plotting:
sb.heatmap(test_df)
ax = sb.plt.gca()
for label in (ax.get_xticklabels() + ax.get_yticklabels()):
label.set_fontname('Arial')
label.set_fontsize(3)
sb.plt.savefig("../outputs/caesar_imposter_heatmap.pdf")
sb.plt.clf()
verifier = Verification(random_state=1000,
metric=dm,
n_features=10000,
n_dev_pairs=0,
n_test_pairs=99999999,
vector_space_model=vsm,
balanced_pairs=False,
control_pairs=False)
logging.info("Starting verification [train / test]")
verifier.vectorize(X_dev, X_test)
train_results, test_results = verifier.predict(filter_imposters=False)
logging.info("Computing results")
test_df = verifier.get_distance_table(verifier.test_dists, verifier.test_pairs, "test")
test_df.to_csv("../outputs/caesar_test.csv")
test_df = pd.read_csv("../outputs/caesar_test.csv")
test_df = test_df.set_index("id")
test_df = test_df.applymap(lambda x:int(x*1000)).corr()
# heatmap plotting:
sb.heatmap(test_df)
ax = sb.plt.gca()
for label in (ax.get_xticklabels() + ax.get_yticklabels()):
label.set_fontname('Arial')
label.set_fontsize(3)
sb.plt.savefig("../outputs/caesar_imposter_heatmap.pdf")
sb.plt.clf()
metric=dm,
sample_authors=False,
n_features=5000,
n_dev_pairs=10000,
em_iterations=100,
vector_space_model=vsm,
weight=0.2,
eps=0.01,
norm="l2",
balanced_pairs=True)
logging.info("Starting verification [train / test]")
verifier.vectorize(X_dev)
dev_results = verifier.fit()
logging.info("Computing results")
test_df = verifier.get_distance_table(verifier.dev_dists,
verifier.dev_pairs, "dev")
ax = plt.Subplot(fig, outer_grid[cnt])
linkage_matrix = linkage(test_df, 'complete')
f = dendrogram(linkage_matrix,
truncate_mode='lastp',
show_leaf_counts=True,
ax=ax,
orientation='right',
labels=test_df.columns,
leaf_font_size=0.5,
link_color_func=None,
color_threshold=np.inf)
tickL = ax.yaxis.get_ticklabels()
for t in tickL:
t.set_fontsize(1)
t.set_color('grey')
metric=dm,
sample_authors=False,
n_features=5000,
n_dev_pairs=10000,
em_iterations=100,
vector_space_model=vsm,
weight=0.2,
eps=0.01,
norm="l2",
balanced_pairs=True)
logging.info("Starting verification [train / test]")
verifier.vectorize(X_dev)
dev_results = verifier.fit()
logging.info("Computing results")
test_df = verifier.get_distance_table(verifier.dev_dists, verifier.dev_pairs, "dev")
ax = plt.Subplot(fig, outer_grid[cnt])
linkage_matrix = linkage(test_df, 'complete')
f = dendrogram(linkage_matrix,
truncate_mode='lastp',
show_leaf_counts=True,
ax=ax,
orientation='right',
labels=test_df.columns,
leaf_font_size=0.5,
link_color_func=None,
color_threshold=np.inf)
tickL = ax.yaxis.get_ticklabels()
for t in tickL:
t.set_fontsize(1)
t.set_color('grey')