Closed kelvin-ksl closed 1 year ago
In make_experimanet
to create a experiment, then you can feed the training data. After run
the experiment, you can predict the test data using the model
which are obtained from experiment.run()
. The process is similar to 'fit'(for training dataset) and 'predict'(for test dataset) in sklearn. Why do you want to use 2 dataframes? And where should they be used?
I am making an algorithm for anomaly detection and want to train it with normal data only and then test it with anomalous data.
How to use 2 dataframes in hyperts? I'm trying to use a dataframe for training and another for testing, but I'm having problems. Concatting the dataframes and then splitting is not an option.