This section shows the input table, SQL query, and output tables of an example using TD_XGBoost for a JSON tree model string in multiple rows.

## InputTable

The input is a housing_full dataset sample, with 13 feature columns and a target (response) column 'medv'.

The following table shows only a part of the dataset.

crim | zn | indus | chas | nox | rm | age | dis | rad | tax | ptratio | b | lstat | medv | partition_id |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|

0.04379 | 80.0 | 3.37 | 0.0 | 0.398 | 5.787 | 31.1 | 6.6115 | 4.0 | 337.0 | 16.1 | 396.9 | 10.24 | 19.4 | 5 |

0.00632 | 18.0 | 2.31 | 0.0 | 0.538 | 6.575 | 65.2 | 4.09 | 1.0 | 296.0 | 15.3 | 396.9 | 4.98 | 24.0 | 31 |

0.05789 | 12.5 | 6.07 | 0.0 | 0.409 | 5.878 | 21.4 | 6.498 | 4.0 | 345.0 | 18.9 | 396.21 | 8.1 | 22.0 | 5 |

0.02731 | 0.0 | 7.07 | 0.0 | 0.469 | 6.421 | 78.9 | 4.9671 | 2.0 | 242.0 | 17.8 | 396.9 | 9.14 | 21.6 | 31 |

0.13554 | 12.5 | 6.07 | 0.0 | 0.409 | 5.594 | 36.8 | 6.498 | 4.0 | 345.0 | 18.9 | 396.9 | 13.09 | 17.4 | 5 |

0.02729 | 0.0 | 7.07 | 0.0 | 0.469 | 7.185 | 61.1 | 4.9671 | 2.0 | 242.0 | 17.8 | 392.83 | 4.03 | 34.7 | 31 |

0.12816 | 12.5 | 6.07 | 0.0 | 0.409 | 5.885 | 33.0 | 6.498 | 4.0 | 345.0 | 18.9 | 396.9 | 8.79 | 20.9 | 5 |

0.03237 | 0.0 | 2.18 | 0.0 | 0.458 | 6.998 | 45.8 | 6.0622 | 3.0 | 222.0 | 18.7 | 394.63 | 2.94 | 33.4 | 31 |

0.08826 | 0.0 | 10.81 | 0.0 | 0.413 | 6.417 | 6.6 | 5.2873 | 4.0 | 305.0 | 19.2 | 383.73 | 6.72 | 24.2 | 5 |

0.02985 | 0.0 | 2.18 | 0.0 | 0.458 | 6.43 | 58.7 | 6.0622 | 3.0 | 222.0 | 18.7 | 394.12 | 5.21 | 28.7 | 31 |

## SQL Call

SELECT * FROM TD_XGBoost ( ON housing_full PARTITION BY ANY OUT TABLE MetaInformationTable(xgb_out) USING ResponseColumn('medv') InputColumns('[0:3]') MaxDepth(10) MinNodeSize(1) NumParallelTrees(2) ModelType('REGRESSION') Seed(1) RegularizationLambda(1000) LearningRate(0.8) NumBoostRounds(1) ColumnSampling(1.0) ) AS dt;

## Output

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