spam_classification_model.py

## The model script is no longer needed, it is left for visibility purposes only


##TODO: Improve model!

# import pandas as pd
# import pickle
# from sklearn.feature_extraction.text import CountVectorizer
# from sklearn import svm
# from sklearn.model_selection import train_test_split

# df = pd.read_excel("Email_data.xlsx")

# df = df[["Label", "Text"]]

# X = df["Text"]
# y = df["Label"]

# X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)

# cv = CountVectorizer()
# features = cv.fit_transform(X_train)

# pickle.dump(cv, open("transform.pkl", "wb"))

# model = svm.SVC()
# model.fit(features, y_train)

# pickle.dump(model, open("spam_classification_model.pkl", "wb"))