Table 5 Analysis of ablation experiment results.

From: Information flow optimization for adaptive neighbor selection graph embedding

Dataset

Metric

\(GF_R\)

\(GF_L\)

\(GF_{NOL}\)

\(GF_{NOH}\)

\(\text{GF}_{\text{AVT}}\)

\(GF_{NONH}\)

GF

AMiner

Macro-F1

0.863

0.885

0.872

0.857

0.854

0.866

0.903

Micro-F1

0.864

0.883

0.874

0.853

0.876

0.865

0.908

ROC-AUC

0.785

0.793

0.793

0.772

0.792

0.790

0.811

F1

0.784

0.782

0.784

0.745

0.775

0.782

0.786

DBLP

Macro-F1

0.883

0.894

0.913

0.892

0.903

0.915

0.945

Micro-F1

0.882

0.892

0.926

0.897

0.915

0.928

0.952

ROC-AUC

0.854

0.881

0.870

0.844

0.875

0.874

0.899

F1

0.856

0.875

0.877

0.836

0.882

0.861

0.899

IMDB

Macro-F1

0.762

0.773

0.765

0.753

0.762

0.771

0.784

Micro-F1

0.748

0.787

0.774

0.746

0.781

0.775

0.796

ROC-AUC

0.924

0.932

0.922

0.914

0.925

0.932

0.960

F1

0.935

0.937

0.923

0.919

0.938

0.935

0.954