Sentence examples for decision tree induction from inspiring English sources

The decision tree induction and broader relation types meet the uniqueness and completeness criteria.

Pruning decision trees is a useful technique for improving the generalization performance in decision tree induction, and for trading accuracy for simplicity in other applications.

In this paper a co-processor for the hardware aided decision tree induction using evolutionary approach (EFTIP) is proposed.

Therefore, we present a new approach for problem solving using decision tree induction based on intuitionistic fuzzy sets in this paper.

Decision tree induction is applied for the transformation of this hidden knowledge into easily in terpretable rule base to represent the operation regions of the process.

Then, we design a decision tree induction algorithm POSC4.5, based on C4.5, that uses only positive and unlabeled examples and we give experimental results for this algorithm.

Their work considers the case of Decision Trees induction on 26 different data-sets.

Last, this paper characterizes the parallelized decision-tree induction program.

Decision-tree induction is a classification method that represents the induced knowledge through a hierarchical tree.

Some well-known algorithms for decision-tree induction are C4.5 [1] and CART [2].

It uses the well-known C4.5 decision-tree induction algorithm [1].