This is a simple SPAM/HAM Classification from a list of messages.
What could be a perfect way to utilize unfortunate lockdown period? Like most of you, I spend my time in cooking, coding and reading some latest research papers on weekends. So i got more interest on Data Science,and i have started research on that and learnt Data Science and to explore more i started Projects on ML and NLP. This is one of my simple NLP projects Classifying SPAM or HAM depending on message
I have collected a dataset with messages containing both SPAM and HAM messages, Now SPAM is taken as 1 and HAM is taken as 0 for classification
This project is divided into two parts:
1. Pre-Processing:
- Tokenization — convert sentences to words
- Removing unnecessary punctuation, tags
- Removing stop words — frequent words such as ”the”, ”is”, etc. that do not have specific semantic
- Stemming — words are reduced to a root by removing inflection through dropping unnecessary characters, usually a suffix.
- Lemmatization — Another approach to remove inflection by determining the part of speech and utilizing detailed database of the language.
- Bag of Words
- TF-IDF
2. Model Building:
- From the vectors we have got we will build a model
- From the entire data we will split in to train and test data.
- we will train a model using train data, here we used Naive Bayes Classifier for SPAM/HAM Classification.
- After Training we validate a model using Test data.
- Observe the metrics
The Code is written in Python 3.7