Optimizing the Autoencoder Strategy
What is the best value to use for threshold 
? In the last section, we adopted 
based on our experience. However, is this the best value for 
? Threshold , in this case, is not automatically optimized via the training procedure. It is just a static parameter external to the training algorithm. In KNIME Analytics Platform, it is also possible to optimize static parameters outside of the Learner nodes.
Optimizing Threshold 
Threshold is defined on a separate subset of data, called the optimization set. There are two options here:
- If an optimization set with labeled fraudulent transactions is available, the value of threshold is optimized against any accuracy measure for fraud detection.
- If no labeled fraudulent transactions are available in the dataset, the value of threshold is defined as a high percentile of the reconstruction errors on the optimization set.
During the data preparation phase, we generated three data subsets...
