Decision tree is an important tool for classification in data mining. Many algorithms have been proposed to induce decision trees and most of them involve two phases, a growing phase and a pruning phase. In this paper, we concentrate on the pruning problem. We find that with the ultimate aim of selecting the best sub-tree with the minimal error for a separate test set, the problem can be formulated as an integer program with a nice structure. By exploiting the special structure of this integer program, we propose several interesting algorithms to identify the optimal sub-tree, including the one that is essentially the same as the well-known bottom-up pruning method with computational complexity of O(n). A new optimality proof of the above a...
In this work, we present a new bottom-up algorithm for decision tree pruning that is very e cient (r...
We encode the problem of learning the optimal decision tree of a given depth as an integer optimizat...
<p><b>A</b>: A typical decision tree. A sequence of choices between ‘U’ (left, green) and ‘I’ (right...
AbstractPruning decision trees is a useful technique for improving the generalization performance in...
The pruning phase is one of the necessary steps in decision tree induction. Existing pruning algorit...
This paper presents a study of one particular problem of decision tree induction, namely (post-)prun...
This paper is concerned with the optimal constrained pruning of decision trees. We present a novel 0...
In this paper, we address the problem of retrospectively pruning decision trees induced from data, a...
This paper compares five methods for pruning decision trees, developed from sets of examples. When u...
Top-down induction of decision trees has been observed to suer from the inadequate functioning of th...
To date, decision trees are among the most used classification models. They owe their popularity to ...
Abstract. Decision tree induction techniques attempt to find small trees that fit a training set of ...
Pruning is one of the key procedures in training decision tree classifiers. It removes trivial rules...
Decision tree is a divide and conquer classification method used in machine learning. Most pruning m...
Abstract — Decision trees are few of the most extensively researched domains in Knowledge Discovery....
In this work, we present a new bottom-up algorithm for decision tree pruning that is very e cient (r...
We encode the problem of learning the optimal decision tree of a given depth as an integer optimizat...
<p><b>A</b>: A typical decision tree. A sequence of choices between ‘U’ (left, green) and ‘I’ (right...
AbstractPruning decision trees is a useful technique for improving the generalization performance in...
The pruning phase is one of the necessary steps in decision tree induction. Existing pruning algorit...
This paper presents a study of one particular problem of decision tree induction, namely (post-)prun...
This paper is concerned with the optimal constrained pruning of decision trees. We present a novel 0...
In this paper, we address the problem of retrospectively pruning decision trees induced from data, a...
This paper compares five methods for pruning decision trees, developed from sets of examples. When u...
Top-down induction of decision trees has been observed to suer from the inadequate functioning of th...
To date, decision trees are among the most used classification models. They owe their popularity to ...
Abstract. Decision tree induction techniques attempt to find small trees that fit a training set of ...
Pruning is one of the key procedures in training decision tree classifiers. It removes trivial rules...
Decision tree is a divide and conquer classification method used in machine learning. Most pruning m...
Abstract — Decision trees are few of the most extensively researched domains in Knowledge Discovery....
In this work, we present a new bottom-up algorithm for decision tree pruning that is very e cient (r...
We encode the problem of learning the optimal decision tree of a given depth as an integer optimizat...
<p><b>A</b>: A typical decision tree. A sequence of choices between ‘U’ (left, green) and ‘I’ (right...