BNDC is a network score that can be used for both continuous and discrete variables. For continuous variables, this uses the BNRC score function to calculate scores for these variables.

Parameters

The following parameters (arguments) can be specified for this function.

prop=n

Property output type. This changes properties to be stored in edges and nodes after the estimation.
0: standard.
1: less information (simple) for the contitous or discrete only variable data set.

hyper_bg=x

hb=x

hb value for the hyperparameter range. The hyperparameter β is determined by the grid search. The grid search starts from β = 10^hb and then decreases the value such as β = 10^{hb − (i × hi )}, where i = 1, 2, ...., hn. (default: x = 2.0)

hyper_inc=x

hi=x

hi value for hyperparameter range. See explanation of hyper_bg. (default: x = 0.4)

hyper_n=n

hn=n

hn value for hyperparameter range. See explanation of hyper_bg. (default: n = 21)

linear

Linear mode. This is short for "hb=2.0,hi=1.0,hn=2".

lv=n

Precalculation level of the BNRC score. n = 0 ∼ 3 can be specified. (default: n = 3)

outer=x

Width of the outer region of the value range for B-spline nonparametric regression. (default: x = 0.0000001)

ecv_clip=x

Replaces the clipped edge contribution value with the specified value. Value x can be a specific real value or "nan".

max_loops=n

The maximum number of loops for parameter estimation by the back fitting algorithm. (default: n = 100)

stop

If specified, the algorithm stops if the parameter estimation is not converged.

verbose=n

v=n

Verbose level. By defalt, n=0.

Network Scores | INGOR Manual