spam-classification

The SMS Spam Collection is a set of SMS tagged messages that have been collected for SMS Spam research. It contains one set of SMS messages in English of 5,574 messages, tagged acording being ham (legitimate) or spam.

Built With

Python 3.6
Apache Spark
PySpark- Python API for Apache Spark
Jupyter Notebook

Dependencies

To use PySpark components

!pip install pyspark

Approach:

Pre Processing:

we removed the unwanted expression from the data set
we Tokenized it and used count vectorizer to form feature.
we converted the string label to integer format.
we used differnt algorithm of classification such as:
- Random Forest Classification
- Logistic Regression
- Naive Bayes Classification
- K Mean clustering
- Support Vector Machine

Result

algorithm	accuracy
Random Forest Classification	0.94
Logistic Regression	0.95
Naive Bayes:	0.98
Support Vector Machine	0.96
K Mean clustering	0.81

Contributing

There are no specific guidlines for contibuting. If you see something that could be improved, send a pull request! If you think something should be done differently (or is just-plain-broken), please create an issue.