Tabular dataΒΆ

The subset of PMLB benchmarks was evaluated for FEDOT, TPOT, MLBox and XGboost baseline. The results and metadata are presented below.

Metadata for datasets

Metrics for prediction

As we can see from the table, the results obtained during the experiments demonstrate the advantage of composite pipelines created by the FEDOT over less sophisticated competitors. The only exception is a single case for regression and classification problems respectively, where the maximum value of the quality metric was obtained using a static pipeline.

Also, the comparison was conducted against the state-of-the-art AutoGluon framework.

Comparison of FEDOT and AutoGluon

There is a small advantage of the FEDOT for F1 and ROC AUC metrics, but the other metrics are near equal.