基于改进三体训练法的半监督专利文本分类方法

胡云青,邱清盈,余秀,武建伟

Semi-supervised patent text classification method based on improved Tri-training algorithm

Yun-qing HU,Qing-ying QIU,Xiu YU,Jian-wei WU

表 1 专利数据集特征选择对比结果(试验1)

Tab.1 Comparsion results of feature selection on patent dataset (Test 1)

分类器 F1 Dim=150 Dim=250 Dim=350 Dim=450 Dim=550 Dim=650 Dim=750 Dim=850 Dim=950 Xgboost IG_New&Xgboost 0.515 0.516 0.516 0.519 0.516 0.518 0.518 0.518 0.518 IG&Xgboost 0.469 0.471 0.471 0.480 0.473 0.474 0.475 0.474 0.475 SVM IG_New&SVM 0.474 0.470 0.475 0.502 0.475 0.471 0.470 0.474 0.474 IG&SVM 0.430 0.432 0.432 0.450 0.441 0.439 0.430 0.432 0.432 NB IG_New&NB 0.420 0.412 0.425 0.431 0.430 0.420 0.424 0.425 0.429 IG&NB 0.362 0.375 0.367 0.370 0.355 0.383 0.352 0.360 0.354