| Keyword | CPC | PCC | Volume | Score | Length of keyword |
|---|---|---|---|---|---|
| decision tree feature importance | 0.44 | 1 | 4815 | 57 | 32 |
| decision | 1.05 | 0.9 | 604 | 69 | 8 |
| tree | 0.52 | 0.2 | 9025 | 82 | 4 |
| feature | 0.26 | 0.9 | 4259 | 6 | 7 |
| importance | 0.47 | 0.9 | 3451 | 75 | 10 |
| Keyword | CPC | PCC | Volume | Score |
|---|---|---|---|---|
| decision tree feature importance | 0.41 | 0.2 | 5854 | 12 |
| decision tree feature importance sklearn | 1.37 | 0.3 | 7724 | 22 |
| decision tree feature importance python | 1.43 | 0.8 | 1241 | 52 |
| decision tree feature importance meaning | 0.47 | 0.5 | 1923 | 39 |
| decision tree feature importance plot | 0.13 | 0.8 | 6497 | 39 |
| decision tree regressor feature importance | 0.1 | 0.7 | 1347 | 55 |
| decision tree regression feature importance | 1.95 | 0.7 | 456 | 23 |
| what is feature importance in decision tree | 1.01 | 0.5 | 1503 | 16 |
| decision tree classifier feature importance | 0.31 | 0.4 | 1925 | 65 |
| scikit learn decision tree feature importance | 0.13 | 0.2 | 3662 | 88 |
| get feature importance decision tree sklearn | 1.68 | 0.6 | 5227 | 49 |
| decision tree using sklearn | 0.15 | 1 | 5414 | 68 |
| implementation of decision tree using sklearn | 0.29 | 0.5 | 7386 | 58 |
| decision tree sklearn documentation | 0.51 | 0.7 | 2058 | 29 |
