Decision Tree Algorithms
Assessment of Decision Tree Algorithms on Student’s Recital
... different decision tree algorithms ID3, J48, Simple CART and Alternating Decision Tree are used and ...new decision tree algorithm which is implemented with different UCI ...
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Performance Evaluation System for Decision Tree Algorithms
... the algorithms date back in the ...history, decision tree algorithms tend to automate the entire process of hypothesis generation and then validation much more completely and in a much more ...
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Computational complexity analysis of decision tree algorithms
... classification algorithms available. Decision tree algorithms are among the successful and widely used technique for classification ...tasks. Decision tree techniques have been ...
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Student’s Performance Analysis using Decision Tree Algorithms
... including decision tree method. In this work, decision trees were used which include BFTree, J48 and ...different Decision tree algorithms ...
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Applying Association Rules and Decision Tree Algorithms with Tumor Diagnosis Data
... and decision tree are interested mining algorithms which can be used to find and explore relations between attributes in a data ...and decision tree algorithms are applied with ...
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A comparative study of reduced error pruning method in decision tree algorithms
... IV. E XPERIMENT , R ESULT AND DISCUSSION In this section, we conducted an experiment using Weka application. Weka is a comprehensive suite of Java class libraries that perform many advanced machine learning and data ...
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Title: Popular Decision Tree Algorithms of Data Mining Techniques: A Review
... 1 [email protected]; 2 [email protected]; 3 [email protected] Abstract— The technologies of data production and collection have been advanced rapidly. As result to that, everything gets ...
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Performance Analysis of Undergraduate Students Placement Selection using Decision Tree Algorithms
... use Decision tree algorithms to predict student selection in ...different Decision tree algorithms used to predict student performance in ...step Decision tree ...
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An Analysis on Performance of Decision Tree Algorithms using Student s Qualitative Data
... -Decision Tree is the most widely applied supervised classification ...of decision tree induction are simple and fast and it can be applied to any ...the decision tree algorithm ...
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Evolutionary design of decision-tree algorithms tailored to microarray gene expression data sets
... of decision trees: instead of proposing a new manually designed method for inducing decision trees, we propose automatically designing decision-tree induction algorithms tailored to a ...
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Evolutionary Design of Decision-Tree Algorithms Tailored to Microarray Gene Expression Data Sets
... that decision trees and SVMs are very different types of algorithms, and the goal of this comparison is not to directly evaluate the effectiveness of HEAD-DT as a method to generate ...
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Wheat Yield Assessment using Decision Tree Algorithms
... by Decision Tree Induction, Rule based classification, classification by Back Propagation, Associative classification ...various algorithms like J48, ID3, Random Tree, JRip, NNge, OneR, PART, ...
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Performance Analysis of Decision Tree Algorithms on Mushroom Dataset
... namely decision tree classification has the task to predict accurately the class to which the data samples belong ...of decision tree classification using ID3, CART, and HT are ...
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ANALYZING EMPLOYEE ATTRITION USING DECISION TREE ALGORITHMS
... of decision trees is their ...a decision tree classifies an instance as belonging to a specific ...a decision tree constitutes a hierarchy of tests, an unknown feature value during ...
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Decision Tree Algorithms for Diagnosis of Cardiac Disease Treatment
... database. Decision tree learning algorithm has been successfully used in expert systems in finding the ...building decision tree, such as ID3, ...for decision making tree ...
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Robustness analysis of diversified ensemble decision tree algorithms for microarray data classification
... k-th tree can only use the genes that have not been selected by the previously created k-1 trees, the quality of k-th tree might be ...Each tree is given the weight of its training clas- sification ...
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Implementation of Artificial Neural Networks and Decision Tree Algorithms for Heart Disease Diagnosis
... So, many researchers carried out their works in heart disease dataset with 13 attributes, and 15 attributes with various data mining methods. In this study, ranking method was used in preprocessing a stage with total of ...
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On the automatic design of decision-tree induction algorithms
... optimising decision-tree algorithms have been made by re- searchers within the last decades, even though the most successful algorithms date back to the mid-80’s and early ...accurate ...
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Comparative Analysis of Serial Decision Tree Classification Algorithms
... the decision T has a class from other source which is not ...constructed tree. With Hunt’s method decision tree is constructed in two phases: tree growth and pruning phases which have ...
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Toward Predictable Performance in Decision Tree-based Packet Classification Algorithms
... Index Terms—Predictability, Packet Classification, Decision Tree Algorithms. I. INTRODUCTION Packet classification is a key functionality for both routers and network middleboxes to provide advanced ...
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