Minor Cleanup of files. Moved to unused folder.

scripts/preprocessing.py

@@ -1,37 +0,0 @@
-import pandas as pd
-import string, re
-from nltk.tokenize import word_tokenize
-from nltk.corpus import stopwords
-import nltk
-from nltk.stem import PorterStemmer, WordNetLemmatizer
-from sentence_transformers import SentenceTransformer
-
-nltk.download('wordnet')
-nltk.download('punkt_tab')
-nltk.download('stopwords')
-
-stop_words = set(stopwords.words('english'))
-
-stemmer = PorterStemmer()
-lemmatizer = WordNetLemmatizer()
-
-model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')
-
-df = pd.read_excel('C:\\Users\\ishaa\\OneDrive\\Documents\\MSU\\Spring 2026\\Data mining\\Project\\sample_data.xlsx', engine='openpyxl')
-
-def clean_text(text):
-    text = text.lower()
-    text = text.translate(str.maketrans('', '', string.punctuation))  # Remove punctuation
-    text = re.sub(r'\W', ' ', text)  # Remove special characters
-    text = ([word for word in word_tokenize(text) if word not in stop_words])
-    text = [stemmer.stem(word) for word in text]
-    text = ' '.join(lemmatizer.lemmatize(word) for word in text)
-    return text
-# print(df.columns)
-
-df['preprocessed'] = df['Plot'].apply(clean_text)
-sample_plot = df['preprocessed'][0]
-print(sample_plot)
-
-embeddings = model.encode(sample_plot)
-print(embeddings)