| Keyword | CPC | PCC | Volume | Score | Length of keyword |
|---|---|---|---|---|---|
| xgboost model fit | 1.25 | 0.6 | 7366 | 38 | 17 |
| xgboost | 0.31 | 0.1 | 5582 | 77 | 7 |
| model | 0.84 | 0.1 | 5239 | 84 | 5 |
| fit | 0.82 | 0.2 | 5991 | 58 | 3 |
| Keyword | CPC | PCC | Volume | Score |
|---|---|---|---|---|
| xgboost model fit | 0.85 | 0.2 | 4052 | 76 |
| xgboost model feature importance | 0.04 | 0.7 | 5530 | 64 |
| xgboost model for regression | 1.06 | 0.4 | 8145 | 67 |
| xgboost model training | 0.15 | 0.1 | 5783 | 27 |
| xgboost model type | 0.41 | 1 | 5640 | 75 |
| xgboost modeling | 0.61 | 0.8 | 4054 | 98 |
| what is feature importance in xgboost | 1.09 | 0.3 | 5202 | 22 |
| xgboost show feature importance | 0.82 | 0.7 | 7477 | 60 |
| xgboost get feature importance | 1.65 | 1 | 7898 | 61 |
| xgboost feature importance gain | 1.98 | 0.7 | 4317 | 97 |
| xgboost feature importance interpretation | 0.64 | 1 | 1700 | 30 |
| xgboost feature importance plot | 1.6 | 0.3 | 616 | 22 |
| how to interpret feature importance xgboost | 1.9 | 0.9 | 7622 | 13 |
| what is xgboost model | 0.01 | 0.6 | 473 | 77 |
| how does xgboost calculate feature importance | 0.7 | 0.3 | 8449 | 49 |
| how xgboost model works | 0.2 | 0.3 | 6179 | 12 |
| xgboost booster feature importance | 1.76 | 0.9 | 9044 | 64 |
| xgboost plot_importance model | 1.47 | 0.1 | 5548 | 13 |
| what type of model is xgboost | 0.98 | 0.4 | 2399 | 52 |
| xgboost importance_type | 0.73 | 0.7 | 1578 | 78 |
| how to implement xgboost | 0.57 | 0.8 | 6212 | 25 |
