https://github.com/aditya-ranjan1234/sms-spam-detector
Checks whether a message is spam or not
https://github.com/aditya-ranjan1234/sms-spam-detector
beginner ml spam-detection
Last synced: 7 months ago
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Checks whether a message is spam or not
- Host: GitHub
- URL: https://github.com/aditya-ranjan1234/sms-spam-detector
- Owner: Aditya-Ranjan1234
- License: gpl-3.0
- Created: 2024-06-01T13:42:01.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-06-02T09:11:19.000Z (over 1 year ago)
- Last Synced: 2025-03-16T07:44:45.818Z (7 months ago)
- Topics: beginner, ml, spam-detection
- Language: Jupyter Notebook
- Homepage:
- Size: 687 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# SMS Spam Detector
SMS Spam Detector is a simple Python script that checks whether a given message is spam or not. It utilizes machine learning techniques to classify messages based on their content.
## Installation
Clone the repository:
```
git clone https://github.com/Aditya-Ranjan1234/SMS_Spam_Detector.git
```
## Usage
To use the SMS Spam Detector, follow these steps:
1. Prepare your message data.
2. Enter the message you want to classify in the end of jupyter notebook.
3. The script will output whether the message is spam or not.
Example:
```
# Enter SMS Message
sms = 'Aft i finish my lunch then i go str down lor. Ard 3 smth lor. U finish ur lunch already?'
transformed_sms = tfidf.transform([transform_text(sms)]).toarray()
for name,clf in clfs.items():
answer=clf.predict(transformed_sms)
print("For ",name)
print("Result",answer)
if(answer[0]==0):
print("ham")
else:
print("spam")
```
## Dataset
The SMS Spam Detector is trained on the [SMS Spam Collection Dataset](https://archive.ics.uci.edu/ml/datasets/SMS+Spam+Collection) available from the UCI Machine Learning Repository. This dataset contains a collection of SMS messages that are labeled as spam or ham (not spam).
## Dependencies
Python 3.x
pandas
numpy
scikit-learn
Installation
## Credits
This code was originally created by CampusX (@campusx-official). \
Many lines of code have been added and modified.