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