GenDataFilter generates a simulated dataset for the given network structure. The network structure can be generated by the RNDNetworkFilter.

Arguments

n=n

The number of samples to generate.

file=file

The generated data set is put in the specified file. The data set is put in GDF format. See the programming document of ytGDF for details.

args={key [ =value ,... ]}

Arguments for outputting the dataset. See the programming document of ytGDF for the available key and values.

types=t₁:t₂: ...

Types of variables. If not specified they are automatically determined at random with the ratio specified by the r argument. t_i is either d and c where i represents the index of variables.

disc=r₁:r₂: ...

The probabilities of the number of categories for discrete variables. r₁ + ... + r_N needs to be 1.0, representing that a discrete variable will have i + 1 categories with probability r_i. If this is not specified, all the discrete variables have two possible values (categories).

r=x

The ratio of discrete variables.

dehybrid

Specifies to save generated data as dynamic model represented by a bipartite graph.

categorical

Discrete variables are regarded as categorical values.

sd=x (default: x=0.3)

Standard deviation of the system noise. The system noise is generated and added to the calculated data using random values of the normal distribution with the specified standard deviation.

osd=x (default: x=0)

Standard deviation of the observation noise. The observation noise is generated and added to the generated data using random values of the normal distribtion with the specified standard deviation. If 0 is specified, no observation noise is added.

func=f₁:f₂:...

The list of function IDs to be assigned for edges.

use_net_func

Use function IDs for edges in node property "model.func" of the input network.

dbn

Shrinking time-expanded DBN model data before writing into a file. This assumes mainly time-expanded DBN networks generated by RNDNetworkFilter with "m=dbn" option.

rand_type= { normal | uniform } (default: rand_type=normal)

EXPERIMENTAL: Type of the random value distribution for noise and nodes with no parents. This only supports continuous variable nodes, and does not support for observation noise.

Filters | INGOR Manual