Description Usage Arguments Value Note Author(s) See Also Examples

This function extracts the structure of a tree from a
`learnPattern`

object.

1 | ```
getTreeInfo(object, which.tree=1)
``` |

`object` |
a |

`which.tree` |
which tree to extract? |

is a list with the following components:

`segment.length` |
the proportion of the time series length used for both predictors and targets. |

`target` |
starting time of the target segment. |

`target.type` |
type of the target segment; 1 if observed series, 2 if difference series. |

`tree` |
Tree structure matrix with seven columns and number of rows equal to total number of nodes in the tree. |

The seven columns of the `tree`

structure matrix are:

`left daughter` |
the row where the left daughter node is; 0 if the node is terminal |

`right daughter` |
the row where the right daughter node is; 0 if the node is terminal |

`split segment` |
start time of the segment used to split the node |

`split type` |
type of the predictor segment used to split the node; 1 if observed series, 2 if the different series are used. 0 if the node is terminal |

`split point` |
where the best split is |

`status` |
is the node terminal (-1) or not (-3) |

`depth` |
the depth of the node |

`prediction` |
the prediction for the node |

For numerical predictors, data with values of the variable less than or equal to the splitting point go to the left daughter node.

Mustafa Gokce Baydogan

1 2 3 4 5 6 | ```
data(GunPoint)
set.seed(71)
## Learn patterns on GunPoint training series with 50 trees
ensemble=learnPattern(GunPoint$trainseries,ntree=50)
getTreeInfo(ensemble, 3)
``` |

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