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Table 4 Results for the discrimination between environmental-or experimental-associated sentences for different classifiers in the Weka package.

From: EnvMine: A text-mining system for the automatic extraction of contextual information

Method

Subset

Original

Classified

Correct

Recall

Precision

F-value

Naive Bayes Multinomial

Exp

828

802

755

91.2%

94.1%

92.6%

Naive Bayes Multinomial

Env

323

349

276

85.4%

79.1%

82.1%

Naive Bayes

Exp

828

692

679

82.0%

98.1%

89.3%

Naive Bayes

Env

323

459

322

96.0%

70.0%

81.0%

Bayes Logistic Regression

Exp

828

796

746

90.0%

93.7%

91.8%

Bayes Logistic Regression

Env

323

355

273

84.5%

76.9%

80.5%

Bayes Net

Exp

828

617

608

73.4%

98.5%

84.1%

Bayes Net

Env

323

534

314

97.2%

58.8%

73.3%

Meta Bagging

Exp

828

752

708

85.5%

94.1%

89.6%

Meta Bagging

Env

323

399

279

86.4%

69.9%

77.3%

Rules, Decision Table

Exp

828

1041

809

97.7%

77.7%

86.6%

Rules, Decision Table

Env

323

110

91

28.2%

82.7%

42.1%

Random Forest

Exp

828

776

735

88.8%

94.7%

91.7%

Random Forest

Env

323

375

282

87.3%

75.2%

80.8%

  1. The column "original" indicates the original distribution of sentences, "classified" shows the results of the classifier as the obtained number of sentences in each category, and "correct" specifies the number of correctly classified sentences.