Credit Card Fraud Detection with Random Forest Algorithm ( Machine Learning)

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  1. What’s our problem?
  2. Why not Decision Trees but Random Forest?
  3. Fraud Detection.
  4. Evaluation of our model.
  • Logistic Regression
  • Decision Trees
  • Support Vector Machines (SVM)
  • Gradient Boosting
  • Neural Networks
  • ‘V’ columns are the columns created with principal component evaluation to offer privacy for sensitive information. This data has still a useful pattern though we will’t understand what’s it directly.
  • The quantity column is a transaction amount.
  • The time column is the time between the primary data in the information set to the precise data.
  • The category column is a label column that claims whether the precise transaction is a fraud or not.
  • The result was positive and we predicted as positive
  • The result was negative and we predicted as positive
  • The result was positive and we predicted as negative
  • The result was negative and we predicted as negative

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