The sample data already loaded in MySQL comes from Kaggle. To train the model using the full dataset, you need to download the dataset and load the dataset into MySQL manually.
You can verify the sample data content in MySQL using:
%%sqlflow SELECT * from creditcard.creditcard limit 5;
Once your dataset is prepared, you can run the below SQL statement to start training. Note that SQLFlow will automatically split the dataset into training and validation sets, the output of evaluation result is calculated using the validation set.
%%sqlflow SELECT * from creditcard.creditcard TRAIN DNNClassifier WITH model.n_classes=2, model.hidden_units=[128,32], train.epoch=100 COLUMN time,v1,v2,v3,v4,v5,v6,v7,v8,v9,v10,v11,v12,v13,v14,v15,v16,v17,v18,v19,v20,v21,v22,v23,v24,v25,v26,v27,v28,amount LABEL class INTO creditcard.creditcard_deep_model;
We can use the trained model to predict new data, e.g. we can choose some positive sample in the dataset to do predict:
%%sqlflow SELECT * from creditcard.creditcard WHERE class=1 PREDICT creditcard.predict.class USING creditcard.creditcard_deep_model;
Then we can get the predict result using:
%%sqlflow SELECT * from creditcard.predict;