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Implements a k-nearest neighbors classifier, tuned via grid search, to identify fraudulent transactions in a credit-card dataset.
<p>The project reads the “Credit_Card_Fraud_Detection.csv” dataset with pandas, examines its structure, and applies StandardScaler to normalize features. It splits data into training and test sets, then uses GridSearchCV to find the best <code data-start=\"6847\" data-end=\"6869\">KNeighborsClassifier</code> hyperparameters. An error-rate vs. k plot illustrates tuning choices,and final evaluation metrics include accuracy_score, classification_report, and confusion_matrix.</p>
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