GitHub - sids07/SMSSpamClassifier-from-NLP-using-RandomForest-and-GradientBoosting-Classifier: Here i simply took SMSSpamClassifier data and using NLTK library along with RandomForest and GradientBoosting Classifier from sklearn.esemble, i classified if that SMS is spam or ham. Firstly, i cleaned raw data removing punctuations, stopwords and tokenizing along with stemming and lemmatizing. Then, moving forward i test vectoring with CountVectorize, N-grams and Tf-Idf vectorizer. And then, moving forward to feature enginnering i add two new features i.e. text length and percentage of punctuations on text.Then evaluate them if it was useful for detecting spam and if transformation was required. Finally it was applied to Gradient Boosting and Random forest classifier along with GridSearch and their performance was evaluated for selecting better hyperparameters using GridSearchCv.

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Here i simply took SMSSpamClassifier data and using NLTK library along with RandomForest and GradientBoosting Classifier from sklearn.esemble, i classified if that SMS is spam or ham. Firstly, i cleaned raw data removing punctuations, stopwords and tokenizing along with stemming and lemmatizing. Then, moving forward i test vectoring with CountVe…

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Name		Name	Last commit message	Last commit date
Latest commit History 1 Commit
CountVectorizer.ipynb		CountVectorizer.ipynb
Gradient Boosting.ipynb		Gradient Boosting.ipynb
GradientBoosting_GridSearchCV.ipynb		GradientBoosting_GridSearchCV.ipynb
Model_selection_GB_RF.ipynb		Model_selection_GB_RF.ipynb
N-grams.ipynb		N-grams.ipynb
RandomForest.ipynb		RandomForest.ipynb
RandomForest_Grid.ipynb		RandomForest_Grid.ipynb
RandomForest_GridSearchCV.ipynb		RandomForest_GridSearchCV.ipynb
SMSSpamCollection.tsv		SMSSpamCollection.tsv
SMSclassifier.ipynb		SMSclassifier.ipynb
Tf-Idf.ipynb		Tf-Idf.ipynb
data_cleaning.ipynb		data_cleaning.ipynb
feature_engineering.ipynb		feature_engineering.ipynb
feature_engineering_transformation.ipynb		feature_engineering_transformation.ipynb
lemmatizing.ipynb		lemmatizing.ipynb
stemming.ipynb		stemming.ipynb