Interpreting Results
Last updated
Last updated
Benchmark results are available for every synthesizer and dataset pair. The returned results are a object.
The results provide a summary of the benchmarking setup, performance during the execution and the overall evaluation. Browse through the tabs below to learn more about what each result means.
These results summarize the setup of your benchmarking run.
Synthesizer
: The name of the synthesizer used to model and create the synthetic data
Dataset
: The name of the dataset that the synthesizer learned to create
Dataset_Size_MB
: The overall size of the dataset when loaded into Python, in MB
If the synthesizer crashed at any point in the process, you will see a NaN
value from that point onwards. For example, if your synthesizer ran out of memory during the training phase, you'll see NaN
values for the model size, sample time, evaluation time and other metrics.
A score of 1 indicates a perfect match, or high quality. A score of 0 indicates that the data is as different as can be. For more information, see the .