bnlearn datasets

This collection consists of 5 structure learning datasets from the Bayesian Network Repository (Scutari, 2010).

Task: The dataset collection can be used to study causal discovery algorithms.

Summary: 

Size of collection: 5 datasets with 3 - 56 columns of various sizes

Task: Causal Discovery

Data Type: Discrete

Dataset Scope: Collection

Ground Truth: Known / Estimated

Temporal Structure: No

License: TBD

Missing Values: No

Missingness Statement: There are no missing values.

Collection: 

The alarm dataset contains the following 37 variables:

CVP (central venous pressure): a three-level factor with levels LOW, NORMAL and HIGH.

PCWP (pulmonary capillary wedge pressure): a three-level factor with levels LOW, NORMAL and HIGH.

HIST (history): a two-level factor with levels TRUE and FALSE.

TPR (total peripheral resistance): a three-level factor with levels LOW, NORMAL and HIGH.

... (33 more variables, see the corresponding .html file)

The binary synthetic asia dataset:

D (dyspnoea), a two-level factor with levels yes and no.

T (tuberculosis), a two-level factor with levels yes and no.

L (lung cancer), a two-level factor with levels yes and no.

B (bronchitis), a two-level factor with levels yes and no.

A(visit to Asia), a two-level factor with levels yes and no.

S (smoking), a two-level factor with levels yes and no.

X (chest X-ray), a two-level factor with levels yes and no.

E (tuberculosis versus lung cancer/bronchitis), a two-level factor with levels yes and no.

The binary coronary dataset:

Smoking (smoking): a two-level factor with levels no and yes.

M. Work (strenuous mental work): a two-level factor with levels no and yes.

P. Work (strenuous physical work): a two-level factor with levels no and yes.

Pressure (systolic blood pressure): a two-level factor with levels <140 and >140.

Proteins (ratio of beta and alpha lipoproteins): a two-level factor with levels <3 and >3.

Family (family anamnesis of coronary heart disease): a two-level factor with levels neg and pos.

The hailfinder dataset contains the following 56 variables:

N07muVerMo (10.7mu vertical motion): a four-level factor with levels StrongUp, WeakUp, Neutral and Down.

SubjVertMo (subjective judgment of vertical motion): a four-level factor with levels StrongUp, WeakUp, Neutral and Down.

QGVertMotion (quasigeostrophic vertical motion): a four-level factor with levels StrongUp, WeakUp, Neutral and Down.

CombVerMo (combined vertical motion): a four-level factor with levels StrongUp, WeakUp, Neutral and Down.

AreaMesoALS (area of meso-alpha): a four-level factor with levels StrongUp, WeakUp, Neutral and Down.

SatContMoist (satellite contribution to moisture): a four-level factor with levels VeryWet, Wet, Neutral and Dry.

... (49 more variables are in the correspondent .html file)

The lizards dataset contains the following 3 variables:

Species (the species of the lizard): a two-level factor with levels Sagrei and Distichus.

Height (perch height): a two-level factor with levels high (greater than 4.75 feet) and low (lesser or equal to 4.75 feet).

Diameter (perch diameter): a two-level factor with levels narrow (greater than 4 inches) and wide (lesser or equal to 4 inches).