A decision node
that specifies some analysis to be carried out on a single attribute value, with one branch and sub-tree for each feasible outcome of the test.
Not every statistical feature can be a decision node
, which depends on the contribution of the entropy and information gain.
It got input from expert opinion nodes and passed output to decision node
. It had same states like expert opinion node.
Minimum cost flow problem The modeling consist of  with side constraints four nodes-source node, decision node
, transformation node and sink node and the use of resources act as side constraints.
(a) A root node, also called a decision node
, represents a choice that will result in the subdivision of all records into two or more mutually exclusive subsets.
2) Backtrack the baseline path by flipping each decision node
to generate new paths.
at each decision node
, C4.5 chooses the optimal split to be the split that has the greatest information gain, gain(S).
Process Clinical data Resuscitation Airway Resuscitation Arterial oxygen saturation (Sa[O.sub.2]) Resuscitation Blood pressure and pulse Resuscitation Core body temperature Response to Urine output resuscitation Drugs Indication for antimicrobials Drugs Pain Investigations Arterial blood gas Investigations Full blood count Investigations Urea and electrolytes Process Decision node
Resuscitation Is an emergency airway required?
Squares represent decision nodes
. The branches at the right side of a decision node
represent the alternative choices.
The split test on each decision node
in the decision tree is generated in one random set, and the split is decided by the quantitative standard splitting threshold [DELTA].
A generalized regression neural network (GRNN) is a probabilistic neural network consisting of an input layer, a hidden layer, a pattern/summation layer, and a decision node
. Each predictor variable has a corresponding input neuron.
In this paper, the proposed fuzzy-decision based Composite event detection algorithm (FL-CED) consists of three parts: first of all, building network topology based on connected dominating sets; the dominant point is local decision node
; then using space-time correlation to cluster the perceived value of the same attribute, screening out the correct data, and identifying the fault node; finally, determining Composite events with decision-making mechanism based on fuzzy-decision.