.idea/.gitignore

@@ -1,2 +0,0 @@
-# Default ignored files
-/workspace.xml

.idea/Pierwsze.iml

@@ -1,8 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<module type="PYTHON_MODULE" version="4">
-  <component name="NewModuleRootManager">
-    <content url="file://$MODULE_DIR$" />
-    <orderEntry type="jdk" jdkName="Python 3.8" jdkType="Python SDK" />
-    <orderEntry type="sourceFolder" forTests="false" />
-  </component>
-</module>

.idea/inspectionProfiles/profiles_settings.xml

@@ -1,6 +0,0 @@
-<component name="InspectionProjectProfileManager">
-  <settings>
-    <option name="USE_PROJECT_PROFILE" value="false" />
-    <version value="1.0" />
-  </settings>
-</component>

.idea/misc.xml

@@ -1,7 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="JavaScriptSettings">
-    <option name="languageLevel" value="ES6" />
-  </component>
-  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.8" project-jdk-type="Python SDK" />
-</project>

.idea/modules.xml

@@ -1,8 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="ProjectModuleManager">
-    <modules>
-      <module fileurl="file://$PROJECT_DIR$/.idea/Pierwsze.iml" filepath="$PROJECT_DIR$/.idea/Pierwsze.iml" />
-    </modules>
-  </component>
-</project>

.idea/vcs.xml

@@ -1,6 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="VcsDirectoryMappings">
-    <mapping directory="$PROJECT_DIR$" vcs="Git" />
-  </component>
-</project>

code.py

@@ -1,21 +1,15 @@
 from collections import defaultdict
 import math
 import pickle
-import re
 
-open_file=('test-A/out.tsv')
-
-#---------------TRAIN START
-
-#Prawdopodobienstwo wylosowania dokumentu
 def calc_class_logprob(expected_path):
     paranormal_classcount=0
     skeptic_classcount=0
-    with open(expected_path,encoding='utf-8') as f:
+    with open(expected_path) as f:
         for line in f:
-            if '1' in line:
+            if 'P' in line:
                 paranormal_classcount += 1
-            if '0' in line:
+            if 'S' in line:
                 skeptic_classcount += 1
 
     paranormal_prob = paranormal_classcount / (paranormal_classcount + skeptic_classcount)
@@ -26,25 +20,15 @@ def calc_class_logprob(expected_path):
 
 def calc_word_count(in_path, expected_path):
     word_counts = {'paranormal':defaultdict(int), 'skeptic': defaultdict(int)}
-    with open(in_path,encoding='utf-8') as in_file, open(expected_path,encoding='utf-8')  as  expected_file:
+    with open(in_path) as in_file, open(expected_path)  as  expected_file:
         for line, exp in zip(in_file, expected_file):
             class_ = exp.rstrip('\n').replace(' ','')
             text, timestamp = line.rstrip('\n').split('\t')
-            text = text.lower()
-            text = re.sub(r'\\n+', " ", text)
-            text = re.sub(r'http\S+', " ", text)
-            text = re.sub(r'\/[a-z]\/', " ", text)
-            text = re.sub(r'[^a-z]', " ", text)
-            text = re.sub(r'\s{2,}', " ", text)
-            text = re.sub(r'\W\w{1,3}\W|\A\w{1,3}\W', " ", text)
-            text = re.sub(r'\W\w{1,3}\W|\A\w{1,3}\W', " ", text)
-            text = re.sub(r'\W\w{1,3}\W|\A\w{1,3}\W', " ", text)
-            text = re.sub(r'^\s', "", text)
-            tokens = text.split(' ')
+            tokens = text.lower().split(' ')
             for token in tokens:
-                if class_ == '1':
+                if class_ == 'P':
                     word_counts['paranormal'][token] += 1
-                elif class_ == '0':
+                elif class_ == 'S':
                     word_counts['skeptic'][token] += 1
     return word_counts
 
@@ -62,14 +46,12 @@ def calc_word_logprobs(word_counts):
             word_logprobs[class_][token] = math.log(word_prob)
     return word_logprobs
 
-#--------------- TRAIN END
 
 def main():
-    paranomal_class_logprob, skeptic_class_logprob = calc_class_logprob("train/expected.tsv")
-    word_counts=calc_word_count("train/in.tsv","train/expected.tsv")
-    word_counts['paranormal'][''] = 0
-    word_counts['skeptic'][''] = 0
+    paranomal_class_logprob, skeptic_class_logprob = calc_class_logprob("F:/UAM/SEMESTR_I_MGR/SYSTEMY_INTELIGENTNE/ic4g/train/expected.tsv")
+    word_counts=calc_word_count("F:/UAM/SEMESTR_I_MGR/SYSTEMY_INTELIGENTNE/ic4g/train/in.tsv","F:/UAM/SEMESTR_I_MGR/SYSTEMY_INTELIGENTNE/ic4g/train/expected.tsv")
     word_logprobs = calc_word_logprobs(word_counts)
     pickle.dump([paranomal_class_logprob, skeptic_class_logprob, word_logprobs], open('naive_base_model.pkl','wb'))
 
+
 main()

code_prediction.py

@@ -1,46 +0,0 @@
-from collections import defaultdict
-import math
-import pickle
-import re
-
-open_file = open('naive_base_model.pkl', 'rb')
-pickle_loaded = pickle.load(open_file)
-paranomal_class_logprob, skeptic_class_logprob, word_logprobs = pickle_loaded
-def prediction(input,output):
-    output_file = open(output,'w')
-    with open(input,encoding='utf-8') as in_file:
-        for line in in_file:
-            temp_paranormal_logprob = paranomal_class_logprob
-            temp_skeptic_logprob = skeptic_class_logprob
-            text, timestamp = line.rstrip('\n').split('\t')
-            text = text.lower()
-            text = re.sub(r'\\n+', " ", text)
-            text = re.sub(r'http\S+', " ", text)
-            text = re.sub(r'\/[a-z]\/', " ", text)
-            text = re.sub(r'[^a-z]', " ", text)
-            text = re.sub(r'\s{2,}', " ", text)
-            text = re.sub(r'\W\w{1,3}\W|\A\w{1,3}\W', " ", text)
-            text = re.sub(r'\W\w{1,3}\W|\A\w{1,3}\W', " ", text)
-            text = re.sub(r'\W\w{1,3}\W|\A\w{1,3}\W', " ", text)
-            text = re.sub(r'^\s', "", text)
-            tokens = text.split(' ')
-            for token in tokens:
-                if token not in word_logprobs['paranormal']:
-                    word_logprobs['paranormal'][token] = -14.78
-                if token not in word_logprobs['skeptic']:
-                    word_logprobs['skeptic'][token] = -15.6
-
-                temp_paranormal_logprob += paranomal_class_logprob + word_logprobs['paranormal'][token]
-                temp_skeptic_logprob += skeptic_class_logprob + word_logprobs['skeptic'][token]
-
-            if temp_paranormal_logprob > temp_skeptic_logprob:
-                output_file.write('1\n')
-            else:
-                output_file.write('0\n')
-##
-def main():
-    prediction('dev-0/in.tsv','dev-0/out.tsv')
-    prediction('test-A/in.tsv/in.tsv','test-A/out.tsv')
-
-main()
-

out_y_hat.tsv

@@ -1,6 +0,0 @@
-Y_hat: -0.0005393564509196473
-Y_hat: -3.9997270479357687
-Y_hat: -4.058054620846149
-Y_hat: -4.948997989328446
-Y_hat: -5.607522681904628
-Y_hat: -5.510496552820199

test_a.tsv

@@ -1,6 +0,0 @@
-0
-0
-0
-0
-0
-0