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Table 1.

Corpus description.

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Table 1 Expand

Table 2.

PAN/CLEF 2012 benchmark description.

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Table 2 Expand

Table 3.

Sentences in novels of BT.

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Table 4.

Number of 3-grams per author (in thousands).

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Table 5.

Novels of author BT.

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Table 6.

Test and training sets of BT.

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Table 7.

Distribution for training and test sets.

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Fig 1.

Average accuracy (%) of SVM vs LR.

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Fig 1 Expand

Table 8.

Accuracy (%) using ALL-features with different split settings.

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Table 8 Expand

Fig 2.

Average accuracy (%) of each type of n-gram for the authors.

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Fig 3.

Average accuracy (%) for 3-grams using all features.

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Table 9.

Accuracy (%) using PCA-features (1, 2, 3, 4 are split settings).

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Table 9 Expand

Fig 4.

Average accuracy (%) for 3-grams using PCA-features.

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Fig 4 Expand

Table 10.

Accuracy using LSA-features (1, 2, 3, 4 are split settings).

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Fig 5.

Average accuracy (%) of 3-grams using LSA features.

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Fig 6.

Average of the accuracy (%) using all features.

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Fig 6 Expand

Fig 7.

Average of the accuracy (%) using PCA features.

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Fig 8.

Average of the accuracy (%) using LSA features.

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Fig 9.

Accuracy (100%) obtained for different sizes.

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Table 11.

Accuracy (%) using 3-grams in complete novels using ALL features.

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Table 12.

Results for different types and sizes of n-grams in complete novels using ALL features.

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Fig 10.

Accuracy (%) averages in models with and without a dimension reduction.

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Table 13.

Precision, recall and F1 in ALL features.

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Fig 11.

PCA visualization of Iris Murdoch (IM) using syntactic relationship 3-gram.

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Fig 12.

PCA visualization of Louis Tracy (LT) using syntactic relationship 3-gram.

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Fig 13.

ROC of Mark Twain (MT) using syntactic relationship 3-gram.

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Fig 14.

AUC of Mark Twain (MT) using syntactic relationship 3-gram via different threshold.

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Table 14.

One-sample T-test results for different types of 3-grams.

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