(y)
| 421 | |
| 422 | |
| 423 | def calculate_gini(y): |
| 424 | unique_labels = np.unique(y) |
| 425 | var = 0 |
| 426 | for label in unique_labels: |
| 427 | count = len(y[y == label]) |
| 428 | p = count / len(y) |
| 429 | var += p ** 2 |
| 430 | return 1 - var |
| 431 | |
| 432 | |
| 433 | class ClassificationTree(DecisionTree): |
no outgoing calls
no test coverage detected