Classification on bank-marketing
90.91AccuracyXGBoost
Evaluation results
| Method | Links | |
|---|---|---|
| XGBoostvalidation_strategy=5-fold cross validation2021.09 | 90.91 | |
| LightGBMvalidation_strategy=5-fold cross validation2021.09 | 90.76 | |
| CAAFEBackbone=XGBoost, n (number of samples)=45.2k, p (number of features)=162025.03 | 90.7 | |
| FeatLLMBackbone=XGBoost, n (number of samples)=45.2k, p (number of features)=162025.03 | 90.7 | |
| LLM-FEBackbone=XGBoost, n (number of samples)=45.2k, p (number of features)=162025.03 | 90.7 | |
| RFvalidation_strategy=5-fold cross validation2021.09 | 90.68 | |
| RRLvalidation_strategy=5-fold cross validation2021.09 | 90.63 | |
| BaseBackbone=XGBoost, n (number of samples)=45.2k, p (number of features)=162025.03 | 90.6 | |
| OpenFEBackbone=XGBoost, n (number of samples)=45.2k, p (number of features)=162025.03 | 90.6 | |
| PLNN(MLP)validation_strategy=5-fold cross validation2021.09 | 90.54 | |
| SBRLvalidation_strategy=5-fold cross validation2021.09 | 90.38 | |
| LRvalidation_strategy=5-fold cross validation2021.09 | 90.13 | |
| CRSvalidation_strategy=5-fold cross validation2021.09 | 90.11 | |
| OCTreeBackbone=XGBoost, n (number of samples)=45.2k, p (number of features)=162025.03 | 90 | |
| C4.5validation_strategy=5-fold cross validation2021.09 | 89.93 | |
| CARTvalidation_strategy=5-fold cross validation2021.09 | 89.83 | |
| SVMvalidation_strategy=5-fold cross validation2021.09 | 88.31 | |
| CORELSvalidation_strategy=5-fold cross validation2021.09 | 88.3 |