Nov 17, 2012 · According to this heuristic information, our algorithm is to pick the attribute that provides more gain ratio and costs less for each selection.
A decision tree algorithm inspired by C4.5 for numeric data that is stable and eective, the post-pruning technique reduces the total cost signicantly, ...
These algorithms deal with only symbolic data. In this paper, we develop a decision tree algorithm inspired by C4.5 for numeric data. There are two major issues ...
A decision tree algorithm inspired by C4.5 with post-pruning and competition for numeric data that considers the tradeoff between test costs and ...
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In this paper, we develop a decision tree algorithm inspired by C4.5 with post-pruning and competition for numeric data. The test cost weighted information gain ...
Nov 17, 2012 · In this paper, we develop an algorithm named Competition Cost-sensitive. C4.5 for numeric data. This algorithm is inspired by C4.5 [6]. C4.5 is ...
This paper studies a number of such algorithms and presents a competition strategy to obtain trees with lower cost. First, we generate a population of decision ...
Apr 4, 2018 · An experimental study for cost complexity pruning and C4.5's error-based pruning that concentrated on pruning with loss minimization and ...
May 5, 2019 · The researchers in. [16] introduced a new decision tree algorithm that was named as competition cost-sensitive C4.5 for numeric data based on C4 ...
Among them, post-pruning is the most commonly used method. However, standard error based pruning methods are not suitable for cost-sensitive learning ...