A spam filter is being designed to classify emails. The model needs to consider the presence of certain words in the email (e.g., "sale," "discount") and their likelihood to indicate spam. Which classifier is more suited for this kind of problem?
- K-Means Clustering
- Naive Bayes
- Random Forest
- Support Vector Machine (SVM)
Naive Bayes is effective for text classification tasks, such as spam filtering, as it models the likelihood of words (e.g., "sale," "discount") indicating spam or non-spam, considering word presence.
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