Evaluation.DAG: Evaluation function for the estimated DAG.

In TransGraph: Transfer Graph Learning

Evaluation function for the estimated DAG.

Description

Evaluation function for the estimated DAG.

Usage

Evaluation.DAG(estimated.adjace, true.adjace, type.adj=2)

Arguments

estimated.adjace	The target data, a n * p matrix, where n is the sample size and p is data dimension.
true.adjace	The auxiliary data in K auxiliary domains, a list with K elements, each of which is a nk * p matrix, where nk is the sample size of the k-th auxiliary domain.
type.adj	The type of adjacency matrix. 1: the entries of matrix contains just two value, 0 and 1, which indicate the existence of edges; 2 (default): the matrix also measures connection strength, and 0 means no edge.

Value

A result list including Recall, FDR, F1score, MCC, Hamming Distance,and estimated error of adjacency matrix on F-norm.

Author(s)

Ruixaun Zhao [e-mail].

References

Zhao, R., He X., and Wang J. (2022). Learning linear non-Gaussian directed acyclic graph with diverging number of nodes. Journal of Machine Learning Research.

TransGraph documentation built on Oct. 19, 2023, 5:06 p.m.