bayesian filtering

How to Implement Bayesian Filtering in Email Marketing?

Implementing Bayesian filtering involves several steps:
Data Collection: Gather a comprehensive dataset of labeled emails to train the filter.
Algorithm Selection: Choose a Bayesian algorithm that suits your needs, such as Naive Bayes.
Training: Train the algorithm using your dataset, ensuring a balanced representation of spam and ham emails.
Testing: Validate the filter's accuracy using a separate test dataset and make adjustments as needed.
Deployment: Integrate the trained filter into your email marketing platform to start filtering incoming emails.

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