Fraud Detection - Credit Card
Fraud or genuine transaction
@kaggle.yashpaloswal_fraud_detection_credit_card
Fraud or genuine transaction
@kaggle.yashpaloswal_fraud_detection_credit_card
Content:-
The dataset contains all credit card transaction details.
Details:-
Except all columns class column denotes following:-
Class 0 --> Non fraudulent
class 1 --> fraudulent
Goal:-
The main goal is to build various different algos.
Solving method:-
The given problem statement is comes under binary classification
We have to solve problem using different machine learning algorithm as well as deep learning algorithms
CREATE TABLE creditcard (
  "time" DOUBLE,
  "v1" DOUBLE,
  "v2" DOUBLE,
  "v3" DOUBLE,
  "v4" DOUBLE,
  "v5" DOUBLE,
  "v6" DOUBLE,
  "v7" DOUBLE,
  "v8" DOUBLE,
  "v9" DOUBLE,
  "v10" DOUBLE,
  "v11" DOUBLE,
  "v12" DOUBLE,
  "v13" DOUBLE,
  "v14" DOUBLE,
  "v15" DOUBLE,
  "v16" DOUBLE,
  "v17" DOUBLE,
  "v18" DOUBLE,
  "v19" DOUBLE,
  "v20" DOUBLE,
  "v21" DOUBLE,
  "v22" DOUBLE,
  "v23" DOUBLE,
  "v24" DOUBLE,
  "v25" DOUBLE,
  "v26" DOUBLE,
  "v27" DOUBLE,
  "v28" DOUBLE,
  "amount" DOUBLE,
  "class" BIGINT
);Anyone who has the link will be able to view this.