MaxPrestige/credit-card-fraud-CLEAN

📦 Dataset Card: credit-card-fraud-CLEAN

Original Dataset: "https://huggingface.co/datasets/dazzle-nu/CIS435-CreditCardFraudDetection"

New Features

• category (float): The category of the transaction. Mapping:

  {
    'entertainment': 0.0,
    'food_dining': 1.0,
    'gas_transport': 2.0,
    'grocery_net': 3.0,
    'grocery_pos': 4.0,
    'health_fitness': 5.0,
    'home': 6.0,
    'kids_pets': 7.0,
    'misc_net': 8.0,
    'misc_pos': 9.0,
    'personal_care': 10.0,
    'shopping_net': 11.0,
    'shopping_pos': 12.0,
    'travel': 13.0
  }
  

• amt (float): The price amount of the transaction.
• gender (float): The gender of the the purchaser. Mapping:

  {
    'F': 0.0,
    'M': 1.0
  }
  

• state (float): The state the transaction took place in. Mapping:

  {
    'AK': 0.0,
    'AL': 1.0,
    'AR': 2.0,
    'AZ': 3.0,
    'CA': 4.0,
    'CO': 5.0,
    'CT': 6.0,
    'DC': 7.0,
    'DE': 8.0,
    'FL': 9.0,
    'GA': 10.0,
    'HI': 11.0,
    'IA': 12.0,
    'ID': 13.0,
    'IL': 14.0,
    'IN': 15.0,
    'KS': 16.0,
    'KY': 17.0,
    'LA': 18.0,
    'MA': 19.0,
    'MD': 20.0,
    'ME': 21.0,
    'MI': 22.0,
    'MN': 23.0,
    'MO': 24.0,
    'MS': 25.0,
    'MT': 26.0,
    'NC': 27.0,
    'ND': 28.0,
    'NE': 29.0,
    'NH': 30.0,
    'NJ': 31.0,
    'NM': 32.0,
    'NV': 33.0,
    'NY': 34.0,
    'OH': 35.0,
    'OK': 36.0,
    'OR': 37.0,
    'PA': 38.0,
    'RI': 39.0,
    'SC': 40.0,
    'SD': 41.0,
    'TN': 42.0,
    'TX': 43.0,
    'UT': 44.0,
    'VA': 45.0,
    'VT': 46.0,
    'WA': 47.0,
    'WI': 48.0,
    'WV': 49.0,
    'WY': 50.0
  }
  

• lat (float): The lattitude the transaction took place in.
• long (float): The longitude the transaction took place in.
• city_pop (float): The population of the city, the transaction took place in.
• merch_lat (float): The lattitude of the merchant that the transaction took place in.
• merch_long (float): The longitude of the merchant that the transaction took place in.
• is_fraud (float): Indication of the transaction as fraudulent (1.0) or non-fraudulent (0.0).

Intended Uses

• Fraudulent Credit Card Transaction prediction models
• Financial data analysis
• Educational and research purposes

Citation

If you use this dataset in your research or application, please cite the original source and this dataset card.