Klasifikacijska stabla

Damiš, Anja (2016) Klasifikacijska stabla. Diploma thesis, Faculty of Science > Department of Mathematics.

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Abstract

The method of classification trees is based on binary tree. If the condition at a particular node is met, the data belong to the left branch, if condition isn’t met, data belong to the right branch. The criteria for the conditions at the nodes are node impurity measures: classification error, Gini index and cross entropy. Of all the possible splittings, we choose the one that achieves the greatest reduction in node impurity, or one that has the best quality of splitting. Pruning the tree is carried out after the initial growing of the tree in order to avoid overfitting of the data. Of all the possible subtrees, we choose a run of subtrees using the cost-complexity criterion and cross-validation error estimation of each subtree and choose the one with the lowest total error.

Item Type: Thesis (Diploma thesis)
Supervisor: Jazbec, Anamarija
Date: 2016
Number of Pages: 24
Subjects: NATURAL SCIENCES > Mathematics
Divisions: Faculty of Science > Department of Mathematics
Depositing User: Iva Prah
Date Deposited: 20 Oct 2016 09:04
Last Modified: 20 Oct 2016 09:04
URI: http://digre.pmf.unizg.hr/id/eprint/5187

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