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Table 1 Assessment rules

From: Feature combination networks for the interpretation of statistical machine learning models: application to Ames mutagenicity

Type Description
ACTIVATING ACTIVATING nodes are the first occasion in the network path (starting from the bottom) where an active feature has been found and is not deactivated. An activating node can have descendant nodes that are predicted active if their assessed type is not activating (i.e. the node has been deactivated or negated).
DEACTIVATED A DEACTIVATED node is one in which the predicted class is active but the node has an inactive parent. Deactivated nodes can be deactivated by multiple parents.
DEACTIVATING A DEACTIVATING assignment occurs when a child node is predicted active but the current node is predicted inactive. The class has switched from active to inactive so a deactivation has occurred. A deactivating node only deactivates children, not more remote descendants.
NEGATED A NEGATED node is one in which the predicted activity is active, all parents are predicted active but at least one ascendant is inactive. The node is not set to deactivated as a deactivating node can only deactivate a child, thus defining the specific contextual relationship of the deactivation which is a superset of the negated component.
ACTIVITY_IDENTIFIED A node is classified as ACTIVITY_IDENTIFIED when it has an activating descendant. Activity is assigned to the lowest feature in the path not the highest.
IGNORE A node is set to IGNORE when it is predicted inactive and has no impact on the nodes below it.