Contents

A node represents a discrete or a discretized variable. In this latter case, the modeled variable is continuous and thresholds were defined, either automatically or manually, to associate discrete states for each continuous value.

A node must have at least two values (or named states or states), each having a probability distribution for each combination of its parents' values.

You can edit a node via the Node Editor (see screenshot below). In the example, the discrete node Dyspnea, which has two values (Yes and No), is being edited. As this node has two binary parents, there are four probability distributions describing the probabilistic relationship between Dyspnea and its two parents, TbOrCa and Bronchitis.




This Node Editor consists of two main areas:

  • The area at the top of the box show the name of the node currently being edited. The associated combo box allows you to switch to editing a different node. As the name implies, the "Rename" button renames the current node. It brings up the following dialog box:


Note that you can also rename a node by double-clicking on the node name on the graph.

  • By clicking on the tabs you can modify different properties of the node. 

States

The States panel contains two areas:

  • The area containing the type of the variable/node being edited. Two types are available:
    • Discrete: for the discrete variables
    • Continuous: for the discretized variables with continuous numerical values.
  • The states list edition panel and the associated buttons. A node has at least two states.

Probability Distributions




This panel allows editing the probabilities associated with the node. It contains two areas:

  • The View Mode area that allows displaying and editing the table of conditional probabilities in three forms:
    • probabilistic
    • determinist
    • equations
    • When a database is associated to the network, a third button is available:

As illustrated above, this button replaces the Conditional Probability Table by the corresponding occurrence matrix, taking into account the smoothing factor, if any.

  • The conditional probability table edition area that allows modifying the probabilities associated to the node. It is possible to change the order of the parents by clicking and dragging the name of the parent in the header of the table's left part. Once a parent is reordered, the modifications are propagated in the conditional probability table.
  • When experts are associated with the network, a button Assessment is displayed and is activated when a cell is selected. The border of the cells with assessments becomes green and the icon  displayed in the cell indicates how important is the disagreement between the experts for this cell.





Properties




This panel allows editing four properties of the node. The edition of each property is also available from the node's contextual menu.

  • The color: allows displaying a colored tag on the node, its comment and its monitor. Checking the option or clicking on the preview rectangle allows displaying the color chooser dialog box. Once the color selected, it is displayed inside the rectangle and can be modified again by clicking on the rectangle. To remove the color, you will have to uncheck the option. The Propagate color to the classes button displays a dialog box allowing selecting the classes, associated to the node, on which we want to propagate the color. In this case, all the nodes belonging to these chosen classes will display the same selected color or any if there is no selection.

  • The image: allows displaying an image instead of the node's default representation. Checking the option or clicking on the preview rectangle allows displaying the file chooser dialog box in order to choose the wanted image. The display size is 30*30. If an image is bigger, it will be reduced, if it is smaller, it will be centered. The image will be saved in the network's file. To remove the image, you will have to uncheck the option. The Propagate image to the classes button displays a dialog box allowing selecting the classes, associated to the node, on which we want to propagate the image. In this case, all the nodes belonging to these chosen classes will display the same selected image or any if there is no selection.

  • The temporal index: allows associating a temporal index to the node. This index is a positive or null integer. It allows indicating a temporal order between the nodes that is taken into account by the learning algorithms. A node with a temporal index greater than the temporal index of another node cannot be its ancestor. To remove the index, you will have to uncheck the option. The Propagate index to the classes button displays a dialog box allowing selecting the classes, associated to the node, on which we want to propagate the index. In this case, all the nodes belonging to these chosen classes will have the same index or any if there is no index.

  • The cost: allows associating a cost to the node. This cost is a real number greater or equal to 1 representing the cost of an observation upon a node. The cost is used in the adaptive questionnaire. It is possible to make a node not observable by unchecking the option. In this case, the node will not be proposed in the adaptive questionnaire. It is also possible to use the "not observable" cost to ignore the values of the node that are read in a database (cf. Interactive inference, Batch labeling, Batch joint probability), to indicate the node to update (cf Interactive Bayesian updating), or to indicate the node for which one wants to compute the posterior probability distribution for each case described in a database (cf Batch inference). The Propagate cost to the classes button displays a dialog box allowing selecting the classes, associated to the node, on which we want to propagate the cost. In this case, all the nodes belonging to these chosen classes will have the same cost or will be not observable if there is no cost.

  • The state virtual number: allows replacing the real number of states during the learning with the MDL score. The node's state number has an important impact on the MDL score computed during the structural learning. This allows influencing the network's structural complexity locally to the node. More a node has states the less it has chance of having linked parents during the learning and vice versa. Decreasing this parameter decreases the MDL score of the node and vice versa. The Propagate state virtual number button displays a dialog box allowing selecting the classes, associated to the node, on which we want to propagate the state virtual number. In this case, all the nodes belonging to these chosen classes will have the same state virtual number or any if there is no one.
  • The local structural coefficient: this parameter acts like the network's global structural coefficient but is proper to each node. It can increase or decrease the structural complexity of the network at the node. This parameter acts on the whole MDL score of the node contrary to the state virtual number. More a node has a high MDL score the less it has chance of having linked parents during learning and vice versa. Decreasing this parameter decreases the node's MDL score and vice versa. The Propagate local structural coefficient button displays a dialog box allowing selecting the classes, associated to the node, on which we want to propagate the local structural coefficient. In this case, all the nodes belonging to these chosen classes will have the same local structural coefficient or any if there is no one.

  • The exclusion: a node can be excluded during structural learning, meaning the learning algorithm won't add any arc having this node as extremity. This is particularly useful if you wish to learn the structure of a network on a subset of nodes. The Propagate exclusion button displays a dialog box allowing selecting the classes, associated to the node, on which we want to propagate the exclusion status. In this case, all the nodes belonging to these chosen classes will have been excluded or not.

Classes

This panel allows managing the classes associated to the node. A class is defined as a set of nodes of a network with an associated name. The concept of classes allows to regroup nodes having common properties and to manage globally these properties. A node can belong to several classes at the same time. The classes can be also managed with the class editor. 



The left list contains classes to which the node belongs. The buttons allows adding a class that already exists in the network, to add a new class that does not exist in the network and to delete the selected classes.

Values

This panel allows managing the values associated to the node's states. We can associate a numerical value to each state of the node. These values allow computing an expected numerical value for these nodes, even if these nodes are purely symbolic. It is also possible not to assign a value to certain states. The states without associated value are then excluded from the calculation of the expected value.


The values are used quite like Utility nodes. Indeed, an expected numerical value can be obtained by associating an Utility node to each node, except that the states without values cannot be represented with this kind of node. Thus, these values are used to evaluate the network, to measure the impact of such lever on the quality of the network. However, unlike Utility nodes, these values are not taken in account during the action policies learning. On the other hand, the values are used in the Pearson's linear correlation coefficient.
When the node is continuous and has associated data, a button Generate Values is displayed at the bottom and allows computing automatically the values associated to the sates from the database. Weights are taken into account.

 

State Names

This panel allows managing the long names associated to the node's states. We can associate a long name to each state of the node. These long names can be used in the monitors, reports and during data export as well (saving database, imputation).

Filtered State

This panel allows us to specify if there is or not a filtered state. Only one filtered state is allowed by variable, continuous or discrete. This state is used to represent the cases where the variable does not have a real existence like, for example, an analysis which would be made according to the positive result of a test.

Comment




The last panel allows editing the comment associated to the node. This comment is in HTML. It is possible to add hypertext links, images and to modify the background and foreground colors. The fonts are fully customizable. A complete description of the integrated HTML editor is available. The comment edition is also available from the node's contextual menu.