Upload Inference.py

Inference.py

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+from NoCodeTextClassifier.preprocessing import *
+from sklearn.feature_extraction.text import TfidfVectorizer
+import pandas as pd
+from pathlib import Path
+import joblib
+
+# Input the email
+text = input("Enter the Email: \n")
+
+# load train data
+train_path = Path("./ML Engineer/train.csv")
+df = pd.read_csv(train_path)
+
+# clean the text
+currency_symbols = r'[\$\£\€\¥\₹\¢\₽\₩\₪]'  
+text_cleaner = TextCleaner(currency_symbols)
+df['clean_text'] = df['email'].apply(lambda x: text_cleaner.clean_text(x))
+
+# fit the TfIdfVecotrizer with train data
+vectorizer = TfidfVectorizer(max_features=10000)
+X = vectorizer.fit(df['clean_text'])
+
+# clean the input email
+clean_text = str(text_cleaner.clean_text(text))
+print(f"\nThe clean text is : {clean_text}")
+
+# vectorize the clean email
+y = vectorizer.transform([clean_text])
+
+# Load the model from the file
+loaded_model = joblib.load('email_detection_model.pkl')
+
+# perform prediction of mail
+predictions = int(loaded_model.predict(y)[0])
+predictions = "spam" if predictions==1 else "not_spam"
+
+# print the prediction
+print(f"\nThe prediction is : {predictions}")