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).