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

  • Authors

    • V Maria Antoniate Martinr St. Joseph's College,Trichy-620002TamilnaduIndia
    • Dr. K. David H.H. The Rajah’s College, Pudukkottai, Tamil Nadu, India
    https://doi.org/10.14419/ijet.v7i2.10714

    Received date: March 27, 2018

    Accepted date: April 23, 2018

    Published date: June 12, 2018

  • Data Mining, Trait Emotional Intelligence, FT Tree, J48Graftt, LAD, NB and Random.

  • Abstract

    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.

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  • How to Cite

    Maria Antoniate Martinr, V., & K. David, D. (2018). Performance analysis of students debugging skills with trait emotional intelligence using decision tree based algorithms. International Journal of Engineering and Technology, 7(2), 948-955. https://doi.org/10.14419/ijet.v7i2.10714