444421

run.py

@@ -0,0 +1,149 @@
+#!/usr/bin/env python
+# coding: utf-8
+
+# In[ ]:
+
+
+import pandas as pd
+from sklearn.linear_model import LogisticRegression
+from sklearn.feature_extraction.text import CountVectorizer,TfidfVectorizer
+from sklearn.metrics import accuracy_score
+
+
+# In[ ]:
+
+
+unxz train/in.tsv.xz
+
+
+# In[ ]:
+
+
+f = open("train/in.tsv", "r", encoding='utf-8')
+lines = f.readlines()
+x_train = pd.DataFrame(lines)
+x_train.rename(columns = {0 : 'text'}, inplace = True)
+
+
+# In[ ]:
+
+
+y_train = pd.read_csv('expected.tsv', sep='\t', names=['male'], encoding='utf-8')
+
+
+# In[ ]:
+
+
+tfidf_vectorizer=TfidfVectorizer(use_idf=True, max_df=0.95)
+tfidf_vectorizer.fit_transform(x_train['text'].values)
+x_train_prepared = tfidf_vectorizer.transform(x_train['text'].values)
+
+
+# In[ ]:
+
+
+model = LogisticRegression()
+model.fit(x_train_prepared, y_train)
+
+
+# In[ ]:
+
+
+f = open("dev-0/in.tsv", "r", encoding='utf-8')
+lines_dev_0 = f.readlines()
+x_test_dev_0 = pd.DataFrame(lines_dev_0)
+
+
+# In[ ]:
+
+
+x_test_dev_0.rename(columns = {0 : 'text'}, inplace = True)
+x_test_dev_0_prepared = tfidf_vectorizer.transform(x_test_dev_0['text'].values)
+
+
+# In[ ]:
+
+
+y_dev_0_expected = pd.read_csv('expected.tsv', sep='\t', names=['male'], encoding='utf-8')
+
+
+# In[ ]:
+
+
+y_dev_0_predicted = model.predict(x_test_dev_0_prepared)
+
+file = open('out.tsv', 'w')
+for y in y_dev_0_predicted:
+    file.write(f'{y}\n')
+file.close()
+
+accuracy_dev_0 = accuracy_score(y_expected, y_predicted)
+accuracy_dev_0
+
+
+# In[ ]:
+
+
+f = open("dev-1/in.tsv", "r", encoding='utf-8')
+lines_dev_1 = f.readlines()
+f.close()
+
+
+# In[ ]:
+
+
+x_test_dev_1 = pd.DataFrame(lines_dev_1)
+x_test_dev_1.rename(columns = {0 : 'text'}, inplace = True)
+x_test_dev_1_prepared = tfidf_vectorizer.transform(x_test_dev_1['text'].values)
+
+
+# In[ ]:
+
+
+y_dev_1_expected = pd.read_csv('expected.tsv', sep='\t', names=['male'], encoding='utf-8')
+
+
+# In[ ]:
+
+
+y_dev_1_predicted = model.predict(x_test_dev_1_prepared)
+
+file = open('out.tsv', 'w')
+for y in y_dev_1_predicted:
+    file.write(f'{y}\n')
+file.close()
+
+accuracy_dev_1 = accuracy_score(y_dev_1_expected, y_dev_1_predicted)
+accuracy_dev_1
+
+
+# In[ ]:
+
+
+f = open("test-A/in.tsv", "r", encoding='utf-8')
+lines_testing = f.readlines()
+f.close()
+
+
+# In[ ]:
+
+
+x_testing = pd.DataFrame(lines_testing)
+x_testing.rename(columns = {0 : 'text'}, inplace = True)
+x_testing_prepared = tfidf_vectorizer.transform(x_testing['text'].values)
+
+
+# In[ ]:
+
+
+y_testing_predicted = model.predict(x_testing_prepared)
+
+
+# In[ ]:
+
+
+file = open('out.tsv', 'w')
+for y in y_testing_predicted:
+    file.write(f'{y}\n')
+file.close()
+