Description Usage Arguments Value References Examples

Estimates Boosting of Smooth Trees (BooST)

1 2 3 4 5 6 7 8 9 | ```
smooth_tree(
x,
y,
p = 1,
d_max = 4,
gamma = seq(0.5, 5, 0.01),
node_obs = nrow(x)/200,
random = FALSE
)
``` |

`x` |
Design matrix with explanatory variables. |

`y` |
Response variable. |

`p` |
Proportion of variables tested in each node split (default 1). |

`d_max` |
Number of splits in each tree (default 4). |

`gamma` |
Transiction function intensity. Bigger numbers makes the transition less smoth. The default is a sequence of values (0.5:5) to be randomized in each new node. Multiple values may be supplied in a vector to increase the model randomness. |

`node_obs` |
Equivalent to the minimum number of observations in a termina node for a discrete tree. |

`random` |
If TRUE trees are grown randomly (default = FALSE) |

An object with S3 class "SmoothTree".

`Model` |
A list with all trees. |

`fitted.values` |
Final model fitted values. |

`nvar` |
Number of variables in x. |

`varnames` |
colnames of x to be used in other functions. |

`call` |
The matched call. |

blablabla

1 | ```
## == to be made == ##
``` |

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