Hello

I have a question regarding the calculation of Mu in tree nodes in Boosting tree method, on second step.

I want to understand how to get it manually. I did the first step successfully. But the first step algorythm used on step 2 doesn't give the same result as Statistica

**In regression problem mu of node always equal to average residuals from the previous step, but in classification problem this idea does not provide desired result. **

**For example, on 2nd step I have dependent variable Y**

0.570947 |

-0.42905 |

0.570947 |

-0.42905 |

-0.42905 |

-0.42905 |

0.570947 |

0.119203 |

0.119203 |

0.119203 |

and independent X:

98.655 |

98.701 |

98.399 |

98.032 |

97.962 |

98.981 |

94.024 |

99.41 |

100.327 |

99.014 |

after tree spliting, left node have only 1 point and dependent variable is 0.570946. Why is mu in this node = 1.165356? May be I should calculate any coefficient? Or anything else?

Statistica project and data set are in attachment.