Research Article
Improving Rolling Bearing Fault Diagnosis by DS Evidence Theory Based Fusion Model
Pseudocode 1
Pseudocode of the C4.5 algorithm.
Input: an attribute set dataset D | Output: a decision tree | (a) Tree = | (b) if is “pure” or other end conditions are met, then | (c) terminate | (d) end if | (e) for each attribute do | (f) compute information gain ratio (InGR) | (g) end for | (h) = attribute with the highest InGR | (i) Tree = create a tree with only one node in the root | (j) = generate a subset from except | (k) for all do | (l) subtree = C4.5 () | (m) set the subtree to the corresponding branch of the Tree according to the InGR | (n) end for |
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