Added create_dictionary and main

linear_regression.py

@@ -0,0 +1,26 @@
+from sklearn.feature_extraction.text import TfidfVectorizer
+from sklearn.feature_extraction.text import CountVectorizer
+import sklearn
+import pandas as pd
+import math
+import re
+
+
+
+def create_dictionary(in_path):
+    tfDict = []
+    with open(in_path,encoding='utf-8') as in_file:
+        for line in in_file:
+            for word in re.findall(r"[\w]+",line):
+                tfDict.append(word)
+    return tfDict
+
+
+def main():
+    created_dictionary=create_dictionary("train/in.tsv")
+    #tfidf = TfidfVectorizer(min_df=1,stop_words='english')
+    tfidf = TfidfVectorizer(stop_words='english')
+    x = tfidf.fit(created_dictionary)
+    y = tfidf.transform(x.vocabulary_)
+
+main()