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Split the data into training (70%) and testing (30%) sets.
Example: Stratified sampling ensures target distribution consistency.
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Apply algorithms like SVM, Logistic Regression, KNN, Decision Trees, or Ensemble models like Random Forest and Gradient Boosting.
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