Empirical study of Machine Learning Classifier Evaluation Metrics behavior in Massively Imbalanced and Noisy data.
Gayan K. KulatillekeSugandika SamarakoonPublished in: CoRR (2022)
Keyphrases
- noisy data
- empirical studies
- evaluation metrics
- machine learning
- training data
- precision and recall
- empirical analysis
- input data
- decision trees
- feature selection
- learning algorithm
- support vector machine
- learning from noisy data
- high dimensional
- support vector
- noise tolerant
- training set
- missing data
- classification algorithm
- feature space
- evaluation measures
- class labels
- missing values
- high dimensionality
- information extraction
- imbalanced datasets
- cost sensitive learning
- learning to rank
- text classification
- pairwise
- feature set
- similarity measure
- ensemble learning
- face recognition
- minority class
- natural language processing
- multimedia