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Binary Classification on Public Dataset

100Accuracy

ViT

Updated 18d ago

Evaluation Results

Method
ViT 2025.08	100	100	100
ConViT 2025.08	100	100	100
GlaBoost 2025.08	99.17	98.56	98.91
Mamba 2025.08	98.96	98.29	98.63
GlaBoost 2025.08	98.73	99.01	98.83
CNN 2025.08	98.37	99.01	98.69
GlaBoost 2025.08	98.36	98.52	98.71
XGBoost 2025.08	98.22	97.86	98.04
RoBERTa 2025.08	98.1	98.57	98.33
LlaMA-3.1-70B 2025.08	97.94	96.87	94.94
Transformer 2025.08	97.86	98.9	98.38
GPT-O3 2025.08	97.82	94.74	94.35
BERT 2025.08	97.77	98.39	98.08
Bi-LSTM 2025.08	97.74	97	97.37
GlaBoost 2025.08	97.52	96.83	96.13
LSTM 2025.08	97.44	98.34	97.89
LlaMA-3.1-405B 2025.08	97.19	97.29	97.01
LlaMA-3.1-70B 2025.08	97.11	96.42	94.84
GRU 2025.08	97.08	96.9	96.99
ConViT-Transformer 2025.08	97.03	97.33	97.18
CNN-BERT 2025.08	97.02	96.61	96.81
ConViT-Mamba 2025.08	96.97	96.48	96.72
CNN-LSTM 2025.08	96.96	96.42	96.69
ViT-Mamba 2025.08	96.83	97.38	97.1
GPT-4O 2025.08	96.77	96.44	95.77
Bi-RNN 2025.08	96.72	97.84	97.28
DeepSeek-V3 2025.08	96.69	97.24	96.24
CNN-Transformer 2025.08	96.56	96.81	96.68
LlaMA-3.1-405B 2025.08	96.33	95.49	96.76
DeepSeek-V3 2025.08	96.27	94.4	95.85
GPT-4O 2025.08	96.13	96.02	97.65
GPT-O3 2025.08	96.13	95.72	96.61
GlaBoost 2025.08	96	95.46	95.73
GlaBoost 2025.08	95.82	95.41	95.63
ViT-Transformer 2025.08	95.73	96.9	96.31
DeepSeek-R1 2025.08	95.72	95.03	95.37
LlaMA-3.1-405B 2025.08	95.63	94.8	95.21
RNN 2025.08	95.62	96.72	96.17
DeepSeek-R1 2025.08	95.57	97.29	96.65
CNN-RNN 2025.08	95.41	96.17	95.79
DeepSeek-V3 2025.08	95.12	94.86	95.01
GPT-O3 2025.08	95.11	94.5	94.8
GPT-4O 2025.08	94.92	94.37	94.65
GPT-O3 2025.08	94.76	94.35	94.59
LlaMA-3.1-70B 2025.08	94.65	93.94	94.29
DeepSeek-V3 2025.08	94.48	93.7	94.09
DeepSeek-R1 2025.08	94.38	95.26	94.72
DeepSeek-R1 2025.08	94.15	94.08	94.11
GPT-4O 2025.08	93.91	93.83	93.86
LlaMA-3.1-405B 2025.08	93.52	93.3	93.38
LlaMA-3.1-70B 2025.08	93.14	93.01	93.07
Random Forest 2025.08	78.93	81.77	80.3
Logistic Regression 2025.08	64.37	67.29	65.83
Linear Regression 2025.08	45.72	51.03	48.26