Upsilon-SVR Polynomial Kernel for Predicting the Defect Density in New Software Projects.
Cuauhtémoc López MartínMohammad AzzehAli Bou NassifShadi BanitaanPublished in: ICMLA (2018)
Keyphrases
- software projects
- polynomial kernels
- kernel function
- support vector machine
- support vector regression
- support vector
- software development
- source code
- software engineering
- gaussian kernels
- project management
- effort estimation
- software quality
- software development effort
- development process
- software maintenance
- software systems
- feature space
- kernel methods
- software development projects
- regression model
- feature selection
- case study
- databases
- real world
- machine learning
- finite sets
- linearly separable
- face recognition
- support vector machine svm
- reinforcement learning
- positive definite
- high dimensional feature space
- object oriented
- dimensionality reduction
- hyperplane
- information systems
- input space
- svm classifier