Creating predictive models with Keras
Our data now contains the following columns:
amount, oldBalanceOrig, newBalanceOrig, oldBalanceDest, newBalanceDest, isFraud, isFlaggedFraud, type_CASH_OUT, type_TRANSFER, isNight
Now that we've got the columns, our data is prepared, and we can use it to create a model.
Extracting the target
To train the model, a neural network needs a target. In our case,
isFraud is the target, so we have to separate it from the rest of the data. We can do this by running:
y_df = df['isFraud'] x_df = df.drop('isFraud',axis=1)
The first step only returns the
isFraud column and assigns it to
The second step returns all columns except
isFraud and assigns them to
We also need to convert our data from a pandas
DataFrame to ...