Argumentation-based Explainable Machine Learning (ArgEML): a Real-life Use Case on Gynecological Cancer.
Nicoletta PrentzasAthena GavrielidouMarios NeofytouAntonis C. KakasPublished in: ArgML@COMMA (2022)
Keyphrases
- real life
- machine learning
- pattern recognition
- knowledge acquisition
- machine learning algorithms
- data mining
- feature selection
- machine learning methods
- breast cancer
- model selection
- information extraction
- supervised machine learning
- data analysis
- cancer diagnosis
- early detection
- artificial intelligence
- learning algorithm
- machine learning approaches
- learning tasks
- prostate cancer
- application domains
- learning systems
- synthetic datasets
- semi supervised learning
- text mining
- natural language processing
- formal representation
- active learning
- reinforcement learning
- requirements elicitation
- data sets
- cancer cells
- ovarian cancer
- normal tissue
- inductive learning
- learning problems
- supervised learning
- knowledge representation
- computer science
- natural language
- training data
- decision trees
- real world