(x, y)
| 58 | return model, ssler |
| 59 | |
| 60 | def CART_REGTraining(x, y) : |
| 61 | |
| 62 | model = DecisionTree_CART(tree_type='reg') |
| 63 | |
| 64 | ssler = StandardScaler() |
| 65 | |
| 66 | ssler.fit(x) |
| 67 | |
| 68 | x = ssler.transform(x) |
| 69 | |
| 70 | model.fit(x, y) |
| 71 | |
| 72 | print((model.predict(x) == y).sum() / len(y)) |
| 73 | |
| 74 | return model, ssler |
| 75 | |
| 76 | def KNNTraining(x, y) : |
| 77 |