| import gradio as gr | |
| import re | |
| import joblib | |
| p_spam = joblib.load("p_spam.pkl") | |
| p_non_spam = joblib.load("p_non_spam.pkl") | |
| parameters_spam = joblib.load("parameters_spam.pkl") | |
| parameters_non_spam = joblib.load("parameters_non_spam.pkl") | |
| def classify(message): | |
| message = re.sub("\W", " ", message) | |
| message = message.lower().split() | |
| p_spam_given_message = p_spam | |
| p_non_spam_given_message = p_non_spam | |
| for word in message: | |
| if word in parameters_spam: | |
| p_spam_given_message *= parameters_spam[word] | |
| if word in parameters_non_spam: | |
| p_non_spam_given_message *= parameters_non_spam[word] | |
| if p_spam_given_message > p_non_spam_given_message: | |
| return "Spam" | |
| elif p_non_spam_given_message > p_spam_given_message: | |
| return "Non-Spam" | |
| else: | |
| return "Equal probabilities, human needed to classify this!" | |
| ir = gr.Interface(classify,inputs="text",outputs="text") | |
| ir.launch() |