Description Usage Arguments Details Value References Examples

Compute the cost function of a tree node

1 | ```
Node_cost(y, Inv_Cov_Y, Command)
``` |

`y` |
Output Features for the samples of the node |

`Inv_Cov_Y` |
Inverse of Covariance matrix of Output Response matrix for MRF(Input [0 0;0 0] for RF) |

`Command` |
1 for univariate Regression Tree (corresponding to RF) and 2 for Multivariate Regression Tree (corresponding to MRF) |

In multivariate trees (MRF) node cost is measured as the sum of squares of the Mahalanobis distance to capture the correlations in the data whereas in univariate trees node cost is measured as the sum of Euclidean distance square. Mahalanobis Distance captures the distance of the sample point from the mean of the node along the principal component axes.

cost or entropy of samples in a node of a tree

Segal, Mark, and Yuanyuan Xiao. "Multivariate random forests." Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 1.1 (2011): 80-87.

1 2 3 4 5 6 7 |

```
```

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.