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EGIA: A new node splitting method for decision tree generation: Special application in software fault prediction

  • Published:2021-06 Issue: Volume: Page:
  • ISSN:2214-7853
  • Container-title:Materials Today: Proceedings
  • language:en
  • Short-container-title:Materials Today: Proceedings

Author:

Singh Manpreet,Kumar Chhabra Jitender

Publisher

Elsevier BV

Subject

General Medicine

Reference42 articles.

1. Comparing Fault-Proneness Estimation Models;Bellini,2005

2. A multiobjective module-order model for software quality enhancement;Khoshgoftaar;IEEE Transactions on Evolutionary Computation,2004

3. A review of estimation techniques to reduce testing efforts in software development;Bareja,2015

4. Improving Fault prediction using ANN-PSO in object oriented systems;Kayarvizhy;International Journal of Computer Applications,2013

5. Analyzing the effect of bagged ensemble approach for software fault prediction in class level and package level metrics;Shanthini,2014

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2. Towards improving decision tree induction by combining split evaluation measures;Knowledge-Based Systems;2023-10

3. Univariate machine learning models applied in photovoltaic power prediction using Python;Energy Sources, Part A: Recovery, Utilization, and Environmental Effects;2023-02-12

4. Statistical analysis of various splitting criteria for decision trees;Journal of Algorithms & Computational Technology;2023-01

5. Integrating Knowledge-Driven and Data-Driven Methodologies for an Efficient Clinical Decision Support System;Advances in Medical Technologies and Clinical Practice;2022-11-11
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