Département de Mathématiques et Informatique

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Matière: Apprentissage automatique II

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Decision tree splitting construction !

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When should we stop splitting in the Dtree construction ?

Posté le 01:13, dimanche 8 mai 2016 By abdelghani laib (77 points)
In Apprentissage automatique II


Réponses (3)




Réponse (1)

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Good Question !

Posté le 07:45, dimanche 8 mai 2016 by Imed BOUCHRIKA
In Apprentissage automatique II



Réponse (2)

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decision trees use multiple algorithms to decide to split a node in two or more sub-nodes,in other words, we can say that purity of the node increases with respect to the target variable. Decision tree splits the nodes on all available variables and then selects the split which results in most homogeneous

Posté le 19:06, jeudi 12 déc. 2019 by noussaiba ledjemel (23 points)
In Apprentissage automatique II



Réponse (3)

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A tree is built by dividing the source set, constituting the root node of the tree, into subsets - which constitute the successor children. Splitting is based on a set of splitting rules based on classification characteristics. This process is repeated on each derived subset in a recursive manner called recursive partitioning. Recursion is complete when the subset at the node level all has the same values ​​of the target variable, or when the splitting no longer adds any value to the predictions.

Posté le 21:52, vendredi 3 janv. 2020 by sihem djélamda (9 points)
In Apprentissage automatique II



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