Add to ORKGOne of the major tasks in Data Mining is classification. The growing of Decision Tree from data is a very efficient technique for learning classifiers. The selection of an attribute used to split the data set at each Decision Tree node is fundamental to properly classify objects; a good selection will improve the accuracy of the classification. In this paper, we study the behavior of the Decision Trees induced with 14 attribute selection measures over three data sets taken from UCI Machine Learning Repository
Classification is a widely used technique in the data mining domain, where scalability and efficienc...
Machine learning is now in a state to get major industrial applications. The most important applicat...
Real life problems handled by machine learning deals with various forms of values in the data set at...
Abstract: One of the major tasks in Data Mining is classification. The growing of Decision Tree from...
Decision tree has most widely used for classification. However the main influence of decision tree c...
One approach to induction is to develop a decision tree from a set of examples. When used with noisy...
In [7], a new information-theoretic attribute selection method for decision tree induction was intro...
International audienceDecision trees are efficient means for building classification models due to t...
Several algorithms have been proposed in the literature for building decision trees (DT) for large d...
Abstract. The removal of irrelevant or redundant attributes could benefit us in making decisions and...
Decision tree algorithms have very important place at classification model of data mining. In litera...
Data mining is the process of extracting informative patterns from data stored in a database or data...
Abstract: Decision Tree is a classification method used in Machine Learning and Data Mining. One maj...
Decision Trees are well known classification algorithms that are also appreciated for their capacity...
Some apparently simple numeric data sets cause significant problems for existing decision tree induc...
Classification is a widely used technique in the data mining domain, where scalability and efficienc...
Machine learning is now in a state to get major industrial applications. The most important applicat...
Real life problems handled by machine learning deals with various forms of values in the data set at...
Abstract: One of the major tasks in Data Mining is classification. The growing of Decision Tree from...
Decision tree has most widely used for classification. However the main influence of decision tree c...
One approach to induction is to develop a decision tree from a set of examples. When used with noisy...
In [7], a new information-theoretic attribute selection method for decision tree induction was intro...
International audienceDecision trees are efficient means for building classification models due to t...
Several algorithms have been proposed in the literature for building decision trees (DT) for large d...
Abstract. The removal of irrelevant or redundant attributes could benefit us in making decisions and...
Decision tree algorithms have very important place at classification model of data mining. In litera...
Data mining is the process of extracting informative patterns from data stored in a database or data...
Abstract: Decision Tree is a classification method used in Machine Learning and Data Mining. One maj...
Decision Trees are well known classification algorithms that are also appreciated for their capacity...
Some apparently simple numeric data sets cause significant problems for existing decision tree induc...
Classification is a widely used technique in the data mining domain, where scalability and efficienc...
Machine learning is now in a state to get major industrial applications. The most important applicat...
Real life problems handled by machine learning deals with various forms of values in the data set at...