GitHub / ksdkamesh99 / Spam-Classifier
A Natural Language Processing with SMS Data to predict whether the SMS is Spam/Ham with various ML Algorithms like multinomial-naive-bayes,logistic regression,svm,decision trees to compare accuracy and using various data cleaning and processing techniques like PorterStemmer,CountVectorizer,TFIDF Vetorizer,WordnetLemmatizer. It is implemented using LSTM and Word Embeddings to gain accuracy of 97.84%.
JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ksdkamesh99%2FSpam-Classifier
PURL: pkg:github/ksdkamesh99/Spam-Classifier
Stars: 16
Forks: 11
Open issues: 1
License: mit
Language: Jupyter Notebook
Size: 510 KB
Dependencies parsed at: Pending
Created at: about 5 years ago
Updated at: 3 months ago
Pushed at: over 4 years ago
Last synced at: about 2 months ago
Topics: bag-of-words, count-vectorizer, decision-tree-classifier, embeddings, logistic-regression, lstm-neural-networks, multinomial-naive-bayes, naive-bayes-classifier, porter-stemmer, sms-spam-detection, support-vector-machines, tfidf-vectorizer, wordnetlemmatizer