Local causal and markov blanket induction for causal discovery and feature selection for classification part I: Algorithms and empirical evaluation

Mathematics

• Feature Selection 100%
• Proof by induction 73%
• Evaluation 54%
• Parsimony 25%
• Learning 25%
• Framework 16%
• Experiment 14%
• Experimental Evaluation 13%
• Interpretability 12%
• Large Data Sets 11%
• Classifier 10%
• Loss Function 9%
• Small Sample 9%
• Well-defined 8%
• Sound 8%
• Target 7%
• Evaluate 7%
• Relationships 5%
• Demonstrate 5%
• Performance 5%
• Sufficient Conditions 4%
• Family 4%
• Graph in graph theory 4%
• Form 3%

Engineering & Materials Science

• Feature extraction 57%
• Set theory 28%
• Acoustic waves 11%
• Experiments 10%
• Classifiers 10%