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Table 4 Evaluation on all corpora of SVM classifiers trained with TF-IDF features

From: Supporting systematic reviews using LDA-based document representations

 

Precision

Recall

F1-score

Accuracy

ROC

PRC

Youth development

Linear

0.394799

0.686301

0.50125

0.8628422

0.891629

0.508361

RBF

0.0

0.0

0.0

0.89957353

0.13187

0.055498

POLY

0.0

0.0

0.0

0.8995735

0.15324

0.054825

Cigarette packaging

Linear

0.3679999

0.7076923

0.48421052

0.937896

0.939295

0.477252

RBF

0.0

0.0

0.0

0.9588086

0.06347

0.021359

POLY

0.0

0.0

0.0

0.9588086

0.082638

0.021496

Cooking skill

Linear

0.366666

0.482456

0.416666

0.967365

0.922862

0.328018

RBF

0.0

0.0

0.0

0.9758

0.07937

0.012568

POLY

0.0

0.0

0.0

0.97584233

0.51207

0.500

COPD

Linear

0.59523

0.773195

0.67264

0.909

0.927631

0.720464

RBF

0.0

0.0

0.0

0.8792

0.066893

0.064489

POLY

0.0

0.0

0.0

0.8792

0.1139

0.067315

Proton beam

Linear

0.0574

0.07874

0.0664451

0.881734

0.562028

0.063233

RBF

0.0

0.0

0.0

0.9465

0.442163

0.048747

POLY

0.0

0.0

0.0

0.9465

0.482718

0.05424

  1. RBF radial basis function kernel, POLY polynomial kernel