Reducing numerical precision preserves classification accuracy in Mondrian Forests.
Marc VicunaMartin KhannouzGregory KiarYohan ChatelainTristan GlatardPublished in: IEEE BigData (2021)
Keyphrases
- classification accuracy
- naive bayes
- feature selection
- precision and recall
- training data
- sensitivity analysis
- support vector
- feature space
- training set
- high classification accuracy
- feature set
- high precision
- data sets
- numerical data
- qualitative and quantitative
- genetic algorithm ga
- sufficient conditions
- bayesian networks
- case study
- e learning
- average precision
- numerical methods
- artificial intelligence
- finite difference
- terms of classification accuracy
- real time