| Keyword | CPC | PCC | Volume | Score | Length of keyword |
|---|---|---|---|---|---|
| categorical | 1.54 | 0.2 | 1452 | 10 | 11 |
| Keyword | CPC | PCC | Volume | Score |
|---|---|---|---|---|
| categorical data | 1.85 | 0.2 | 304 | 63 |
| categorical | 0.08 | 0.6 | 108 | 43 |
| categorical imperative | 0.93 | 0.2 | 351 | 51 |
| categorical variable | 1.35 | 0.3 | 2958 | 65 |
| categorical grants | 1.76 | 0.3 | 7518 | 7 |
| categorically definition | 0.8 | 0.5 | 2665 | 6 |
| categorical syllogism | 0.44 | 0.9 | 938 | 33 |
| categorical meaning | 0.53 | 0.4 | 657 | 49 |
| categorical exclusion | 0.51 | 0.4 | 9473 | 87 |
| categorical variable examples | 0.14 | 0.8 | 6478 | 73 |
| categorical vs quantitative | 0.82 | 0.9 | 3825 | 75 |
| categorical perception | 1.58 | 0.5 | 3197 | 12 |
| categorical grants definition | 1.36 | 0.8 | 4714 | 40 |
| categorical imperative definition | 0.78 | 0.6 | 3882 | 10 |
| categorical data examples | 1.85 | 0.8 | 1221 | 53 |
| categorical matlab | 1.53 | 0.2 | 9960 | 79 |
| categoricalnb | 1.47 | 0.2 | 4590 | 7 |
| categorical crossentropy | 1.95 | 1 | 8517 | 95 |
| categorical python | 0.69 | 1 | 5835 | 36 |
| categorical pytorch | 0.41 | 1 | 9982 | 74 |
| categorical accuracy | 1.09 | 0.7 | 2810 | 54 |
| categorical cross entropy keras | 0.41 | 0.6 | 2922 | 51 |
| categorical vs block grants | 1.06 | 0.4 | 1936 | 44 |
| categorical_crossentropy pytorch | 0.98 | 0.3 | 307 | 45 |
