Data Imputation on NPHA
66.35AccuracyLLM-Forest
Evaluation results
| Method | Links | |
|---|---|---|
| LLM-ForestApproach=LLM-based2024.10 | 66.35 | |
| LLM-Forestbase_llm=GPT-42024.10 | 66.35 | |
| TDMApproach=Statistic & Deep Learning2024.10 | 66.29 | |
| TDM2024.10 | 66.29 | |
| Mode ImputationApproach=Statistic & Deep Learning2024.10 | 66.1 | |
| Mode Imputation2024.10 | 66.1 | |
| LLM-TreeApproach=LLM-based2024.10 | 65.57 | |
| LLM-tree2024.10 | 65.57 | |
| RemaskerApproach=Statistic & Deep Learning2024.10 | 65.38 | |
| Remasker2024.10 | 65.38 | |
| GRAPEApproach=Statistic & Deep Learning2024.10 | 65.01 | |
| GRAPE2024.10 | 65.01 | |
| Mean ImputationApproach=Statistic & Deep Learning2024.10 | 64.88 | |
| Mean Imputation2024.10 | 64.88 | |
| LLM-Forestbase_llm=Claude-3.52024.10 | 64.41 | |
| KNNApproach=Statistic & Deep Learning2024.10 | 64.28 | |
| KNNk=72024.10 | 64.28 | |
| LLM-Forestbase_llm=Mixtral2024.10 | 63.91 | |
| Chain-of-ThoughtApproach=LLM-based2024.10 | 63.81 | |
| Chain-of-Thought2024.10 | 63.81 | |
| MICEApproach=Statistic & Deep Learning2024.10 | 62.69 | |
| MICE2024.10 | 62.69 | |
| GAINApproach=Statistic & Deep Learning2024.10 | 60.68 | |
| GAIN2024.10 | 60.68 | |
| LLM-zeroApproach=LLM-based2024.10 | 59.18 | |
| LLM-zero2024.10 | 59.18 | |
| HyperimputeApproach=Statistic & Deep Learning2024.10 | 58.8 | |
| Hyperimpute2024.10 | 58.8 | |
| MiracleApproach=Statistic & Deep Learning2024.10 | 56.05 | |
| Miracle2024.10 | 56.05 |