Using the SMS Spam Collection Dataset from Kaggle. Extracted features using CountVectorizer, used a Logistic Regression pipeline and RandomForestClassifier pipeline and then cross-validation. Used a pre-trained word embedding model spaCy to compare cross-validation f1, recall and precision scores.
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Using the SMS Spam Collection Dataset from Kaggle. Extracted features using CountVectorizer, used a Logistic Regression pipeline and RandomForestClassifier pipeline and then cross-validation. Used a pre-trained word embedding model spaCy to compare cross-validation f1, recall and precision scores.
rahmanshamit/spam-prediction-model
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Using the SMS Spam Collection Dataset from Kaggle. Extracted features using CountVectorizer, used a Logistic Regression pipeline and RandomForestClassifier pipeline and then cross-validation. Used a pre-trained word embedding model spaCy to compare cross-validation f1, recall and precision scores.
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