Anomaly Detection on Synthetic Manufacturing Dataset (test) benchmark leaderboard · SOTA2 Research

Anomaly Detection on Synthetic Manufacturing Dataset (test)

94.4AccuracyRandom Forest

Evaluation Results

Method	Links
Random Forest2025.01		94.4	94.3	100	97.1	98.2	99.9
Vanilla LSTM2025.01		94.3	94.3	99.9	97	91.3	99.4
CNN-LSTM2025.01		93.9	94	99.8	96.8	83	98.1
ANSR-DT (Full)2025.01		93.5	93.6	99.9	96.6	95.5	99.6
CNN-LSTM+Attn2025.01		93.5	93.6	99.9	96.6	84.4	97.6
CNN-LSTM+Symbolic2025.01		93.5	93.6	99.9	96.6	95.5	99.6
Transformer2025.01		93.4	93.4	100	96.6	95.8	99.7
Pure Symbolic2025.01		71.7	99.7	70	82.2	83.5	98.9
One-Class SVM2025.01		31.7	100	26.8	42.3	40	93.9
LSTM Autoencoder2025.01		25.8	100	20.5	34.1	65.1	97.2
Isolation Forest2025.01		23.8	90.6	20.6	33.6	27.8	91.2
LOF2025.01		10.2	100	3.9	7.4	34.5	92.6