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Novel algorithms for cost-sensitive classification and knowledge discovery in class imbalanced datasets with an application to NASA software defects
Michael J. Siers,
Md Zahidul Islam
Data Science Research Unit
DaMRG - Data Mining Research Group
Machine Vision and Digital Health (MaViDH) Research Group
Cyber Security Research Group (CSRG)
Imaging and Sensing Research Group
Health Services Research Group
Computing, Mathematics and Engineering
Research output
:
Contribution to journal
›
Article
›
peer-review
22
Citations (Scopus)
Overview
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Computer Science
Software Defect
80%
Classes
80%
Defect Prediction
60%
Knowledge Discovery
60%
Discovery Process
40%
Classification
20%
Classification (Machine Learning)
20%
Learning Algorithm
20%
Individual Decision
20%
Machine Learning
20%
Source Codes
20%
Software Project
20%
Financial Gain
20%
Extracting Knowledge
20%
Application
20%
Mathematics
Algorithm
80%
Classes
80%
Decision Tree
40%
Prediction
40%
Imbalance
40%
Classification
20%
Minimizes
20%
Calculate
20%
Biochemistry, Genetics and Molecular Biology
Software
100%
Learning
60%
Knowledge Discovery
60%
Classification
20%
Electric Potential
20%
Decision Tree
20%
Pharmacology, Toxicology and Pharmaceutical Science
Tree
20%
Engineering
Individual Decision
20%