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how to understand "Decision tree for classification (text description)"

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Amend
Amend le 14 Avr 2015
Modifié(e) : marwa lagha le 14 Juin 2017
The "Decision tree for classification (text description)" is difficult to understand. Who can give detail explanation.
Thank you

Réponse acceptée

Roberto Herrera-Lara
Roberto Herrera-Lara le 14 Avr 2015
The philosophy of operation of any algorithm based on decision trees is quite simple. In fact, although sometimes containing important differences in the way to do this or that step, any algorithm of this category is based on the strategy of divide and conquer. In general, this philosophy is based on the successive division of the problem into several subproblems with a smaller number of dimensions, until a solution for each of the simpler problems can be found. Based on this principle, the classifiers based on decision trees try to find ways to divide the universe into successively more subgroups (creating nodes containing the respective tests) until each addressing only one class or until one of the classes shows a clear majority do not justifying further divisions, generating in this situation a leaf containing the class majority....
more details here,
http://en.wikibooks.org/wiki/Data_Mining_Algorithms_In_R/Classification/Decision_Trees
http://ocw.mit.edu/courses/sloan-school-of-management/15-097-prediction-machine-learning-and-statistics-spring-2012/lecture-notes/MIT15_097S12_lec08.pdf

Plus de réponses (1)

Amend
Amend le 15 Avr 2015
Modifié(e) : Amend le 15 Avr 2015
The text description for "Decision tree for classification" has some differences from the "if-then-else-end" statement.
For example (from matlab), decision tree for classification
  1. if x3<2.45 then node 2 elseif x3>=2.45 then node 3 else setosa
  2. class = setosa
  3. if x4<1.75 then node 4 elseif x4>=1.75 then node 5 else versicolor
  4. if x3<4.95 then node 6 elseif x3>=4.95 then node 7 else versicolor
  5. class = virginica
  6. if x4<1.65 then node 8 elseif x4>=1.65 then node 9 else versicolor
  7. class = virginica
  8. class = versicolor
  9. class = virginica
from above text, I know "class" represents a leaf. but how can I know leaf "setosa" goes to left branch not right branch from line 1. What does it mean that the word "else" in line 1,3,4 and 6 because it has no sense to tell me left branch or right branch.
  1 commentaire
marwa lagha
marwa lagha le 14 Juin 2017
Modifié(e) : marwa lagha le 14 Juin 2017
it is easier for you to view the decision tree rather that thinking wether it is left or right branch
view(Mdl,'mode','graph');

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