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Performance analysis of students debugging skills with trait emotional intelligence using decision tree based algorithms

机译：基于决策树算法的学生特质情绪智力调试技能的绩效分析

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摘要

Data mining is the extraction of knowledge, meaningful patterns, trends and relationships from huge amount of data stored in repositories. This research focuses on assessing the decision tree techniques like FT tree, J48 graft pruned tree, Random, NB and LAD. A study was conducted on students from post graduation. The questionnaire was designed to test the students debugging skills and Trait Emotional Intelligence. The TEI skills are broadly classified as wellbeing, self-control, emotionality, sociability and global trait EI. The decision trees techniques were applied to the factors like locality, gender, academic performance and students debugging skills. The performances of all the decision tree techniques are compared based on the error measures to find the best suited technique.
机译：数据挖掘是从存储在存储库中的大量数据中提取知识，有意义的模式，趋势和关系。这项研究的重点是评估决策树技术，例如FT树，J48嫁接修剪树，Random，NB和LAD。对毕业后的学生进行了研究。该问卷旨在测试学生的调试技能和特质情绪智力。 TEI技能大致分为幸福，自我控制，情绪，社交能力和全球特质EI。决策树技术被应用于诸如地点，性别，学业成绩和学生调试技能等因素。根据错误度量比较所有决策树技术的性能，以找到最适合的技术。

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