Complete result settings for Retail dataset (table columns are sortable)
The experiments are described in Rooshenas and Lowd, Discriminative Structure Learning of Arithmetic Circuits, AIStats 16

Split Penalty Standard Deviation L1 Penalty Train LL Validation LL Test LL Node# Edge# Feature# Learning Time
10 0.1 2 -10.781008 -10.905318 -10.918711 2549 3706 584 30.955293
10 0.1 1 -10.779042 -10.897178 -10.916361 2742 4119 594 30.765322
10 0.5 2 -10.768489 -10.890084 -10.908020 3402 5557 620 38.239186
10 0.5 1 -10.764746 -10.884026 -10.903869 4502 8129 630 40.968771
10 0.5 0.1 -10.756101 -10.880124 -10.894499 8058 16320 650 47.210822
10 0.1 0.1 -10.773762 -10.897964 -10.915250 2929 4503 602 32.574047
5 0.5 2 -10.735470 -10.861089 -10.876853 23254 51455 758 113.380763
5 0.5 1 -10.723846 -10.855062 -10.863811 30433 67692 818 185.929734
5 0.5 0.1 -10.712359 -10.849894 -10.861178 45015 101380 876 214.131446
5 0.1 2 -10.752122 -10.879527 -10.891449 7417 14688 694 46.495930
5 0.1 0.1 -10.739395 -10.869256 -10.883345 13306 28410 750 73.748787
5 0.1 1 -10.746309 -10.871044 -10.888187 9634 19888 726 52.770976
2 0.5 2 -10.689724 -10.841953 -10.851645 63382 142082 1108 448.409830
2 0.5 1 -10.671868 -10.839353 -10.844606 88982 202420 1268 745.258702
2 0.1 2 -10.715591 -10.850104 -10.867335 33277 73808 952 211.592832
2 0.1 1 -10.700466 -10.844530 -10.854459 42486 95248 1090 289.817940
2 0.1 0.1 -10.691642 -10.846914 -10.853298 54969 123678 1156 383.607682
2 0.5 0.1 -10.656439 -10.828830 -10.845647 132657 306813 1448 1238.593704