Patent ID: 11861519
Assignee: nan
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 9:
10. The system of claim 6,
wherein each node having a true Boolean occurrence value has a numerical value of 1, otherwise a numerical value of 0;
wherein said local probability model of each of said every problem nose is defined by:
identifying a plurality of causing source nodes such that each is a source node connected by a causing edge, representing a causes relationship of the group of relationships, to the problem node;
identifying a plurality of influencing-factor source nodes such that each is a source node connected by an influencing-factor edge, representing an influencing-factor relationship of the group of relationships, to the problem node;
identifying a plurality of influencing combinations of a plurality of Boolean occurrence values of the plurality of influencing-factor source nodes; and
for each influencing combination of the plurality of influencing combinations:
associating with each causing source node of the plurality of causing source nodes a node weight modifying the local probability model, denoted by wk;
associating with the problem node an independent weight modifying the local probability model, denoted by w0; and
associating with the problem node a logistic conditional probability distribution computed by:
computing a plurality of node terms by for each of the plurality of causing source node's multiplying the causing source node's wk by the causing source node's numerical value;
adding the plurality of node terms to produce a parent sum;
adding the parent sum to the independent weight to produce a node sum; and
computing a sigmoid function of the node sum; and wherein training the statistical model comprises deriving values for a plurality of wk and w0 values from the input data.