Spam/Ham Classifier with Handing of Data-Imbalance

Used the Naive-Bayes Algorithm
Use SMOTE[Synthetic Minority Oversampling Technique] to handle the data imbalance
SMOTE (synthetic minority oversampling technique) is one of the most commonly used oversampling methods to solve the imbalance problem. It aims to balance class distribution by randomly increasing minority class examples by replicating them

Distribution of Dataset

CONFUSION MATRIX

F1- Score: 98%

OUTPUT