Abstract: A computing system determines a response to a query. A bin start value and a bin stop value is defined for each bin based on an input bin option. End nodes are split based on the bin start value and the bin stop value of each bin to define a second plurality of end nodes. Each start node of a plurality of start nodes that is connected to each end node of the second plurality of end nodes is identified based on the respective link attributes of a plurality of link attributes. Overlapping start nodes of the plurality of start nodes that overlap at an end node of the second plurality of end nodes are identified based on a predefined overlap query graph that defines a connectivity to identify between a start node and the end node. The identified overlapping start nodes are output as a response to the predefined overlap query graph.

Abstract: A computing system computes a variable relevance using a trained tree model. (A) A next child node is selected. (B) A number of observations associated with the next child node is computed. (C) A population ratio value is computed. (D) A next leaf node is selected. (E) First observations are identified. (F) A first impurity value is computed for the first observations. (G) Second observations are identified when the first observations are associated with the descending child nodes. (H) A second impurity value is computed for the second observations. (I) A gain contribution is computed. (J) A node gain value is updated. (K) (D) through (J) are repeated. (L) A variable gain value is updated for a variable associated with the split test. (M) (A) through (L) are repeated. (N) A set of relevant variables is selected based on the variable gain value.