# One-Class Learning for AI-Generated Essay Detection
## 3 Results
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Setting = Text** & **Precision** & **Recall** & **F1-Score** \\ \hline OneClassSVM (RBF kernel) & 0.6190 & 0.6043 & **0.5917** \\ OneClassSVM (Polynomial kernel) & 0.3102 & 0.3329 & 0.3123 \\ OneClassSVM (Linear kernel) & 0.3102 & 0.3329 & 0.3123 \\ LocalOutlierFactor (3 neighbors) & 0.3641 & 0.4600 & 0.3443 \\ LocalOutlierFactor (5 neighbors) & 0.3409 & 0.4657 & 0.3354 \\ LocalOutlierFactor (10 neighbors) & 0.2582 & 0.4629 & 0.3187 \\ IsolationForest & 0.2511 & 0.4514 & 0.3132 \\ ABOD & 0.2489 & 0.4957 & 0.3314 \\ HBOS & 0.2475 & 0.4900 & 0.3289 \\ AutoEncoder & 0.2426 & 0.4714 & 0.3204 \\ \hline
**Setting = Repetitiveness** & Precision & Recall & F1-Score \\ \hline OneClassSVM (RBF kernel) & 0.5200 & 0.5200 & **0.5199** \\ OneClassSVM (Polynomial kernel) & 0.3988 & 0.4029 & 0.3968 \\ OneClassSVM (Linear kernel) & 0.3972 & 0.4014 & 0.3952 \\ LocalOutlierFactor (3 neighbors) & 0.5369 & 0.5171 & 0.4426 \\ LocalOutlierFactor (5 neighbors) & 0.5697 & 0.5257 & 0.4369 \\ LocalOutlierFactor (10 neighbors) & 0.5752 & 0.5229 & 0.4223 \\ IsolationForest & 0.3971 & 0.4886 & 0.3424 \\ ABOD & 0.2482 & 0.4929 & 0.3301 \\ ABOD & 0.2482 & 0.4929 & 0.3301 \\ ABOD & 0.4578 & 0.4929 & 0.3599 \\ \hline
**Setting = Emotional Semantics** & Precision & Recall & F1-Score \\ \hline OneClassSVM (RBF kernel) & 0.4898 & 0.4900 & **0.4881** \\ OneClassSVM (Polynomial kernel) & 0.3568 & 0.3614 & 0.3562 \\ OneClassSVM (Linear kernel) & 0.3828 & 0.3843 & 0.3824 \\ LocalOutlierFactor (3 neighbors) & 0.5305 & 0.5186 & 0.4663 \\ LocalOutlierFactor (5 neighbors) & 0.5177 & 0.5100 & 0.4501 \\ LocalOutlierFactor (10 neighbors) & 0.5387 & 0.5229 & 0.4684 \\ IsolationForest & 0.4859 & 0.4900 & 0.4499 \\ ABOD & 0.5947 & 0.5100 & 0.3689 \\ HBOS & 0.4830 & 0.4986 & 0.3496 \\ AutoEncoder & 0.5561 & 0.5157 & 0.4094 \\ \hline
**Setting = Readability** & Precision & Recall & F1-Score \\ \hline OneClassSVM (RBF kernel) & 0.7514 & 0.5057 & 0.3459 \\ OneClassSVM (Polynomial kernel) & 0.8218 & 0.7357 & 0.7168 \\ OneClassSVM (Linear kernel) & 0.8244 & 0.7414 & **0.7238** \\ LocalOutlierFactor (3 neighbors) & 0.7134 & 0.6329 & 0.5946 \\ LocalOutlierFactor (5 neighbors) & 0.7055 & 0.6129 & 0.5637 \\ LocalOutlierfactor (10 neighbors) & 0.6382 & 0.5671 & 0.5033 \\ IsolationForest & 0.6904 & 0.6186 & 0.5788 \\ ABOD & 0.2486 & 0.4943 & 0.3308 \\ HBOS & 0.2482 & 0.4929 & 0.3301 \\ AutoEncoder & 0.4845 & 0.4971 & 0.3684 \\ \hline
**Setting = POS** & Precision & Recall & F1-Score \\ \hline OneClassSVM (RBF kernel) & 0.4971 & 0.4971 & **0.4968** \\ OneClassSVM (Polynomial kernel) & 0.4100 & 0.4100 & 0.4100 \\ OneClassSVM (Linear kernel) & 0.3787 & 0.3843 & 0.3771 \\ LocalOutlierFactor (3 neighbors) & 0.5200 & 0.5029 & 0.3673 \\ LocalOutlierFactor (5 neighbors) & 0.5216 & 0.5029 & 0.3652 \\ LocalOutlierFactor (10 neighbors) & 0.5311 & 0.5043 & 0.3681 \\ IsolationForest & 0.2701 & 0.4757 & 0.3247 \\ ABOD & 0.2478 & 0.4914 & 0.3295 \\ HBOS & 0.2482 & 0.4929 & 0.3301 \\ AutoEncoder & 0.3171 & 0.4671 & 0.3297 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Spanish dataset: detection accuracy via 5-fold stratified cross-validation. Highest F1-Score in bold. The Emotional Semantics setting (see Figure 4) showcases 331 (HBOS), 312 (ABOD), 288 (LocalOutlierFactor), 284 (AutoEncoder), 261 (IsolationForest), and 233 (OneClassSVM) incorrectly classified essays. These results show that this setting does not allow for accurate essay detection for all models, as evident by the large amount of miscategorized data. The Readability setting (see Figure 5) presents 268 (ABOD), 183 (HBOS), 170 (OneClassSVM), 116 (LocalOutlierFactor), 109 (AutoEncoder), and 71 (IsolationForest) incorrectly classified essays. This setting is, overall, effective for it yields better results than the Text and Emotional Semantics settings; however, it does not outperform Repetitiveness.