Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

Keyphrases

• Genome-wide Genotyping 100%
• LightGBM 33%
• Missing Genotypes 33%
• Tree-based Methods 33%
• Logistic Regression Method 33%
• Maximal Area 33%
• Epistatic Effect 33%
• Genomic Information 33%
• Marker Preselection 33%
• Machine Settings 33%
• CatBoost 33%
• Dense Neural Network 33%
• Encoding Strategy 33%
• Quality Coding 33%

Biochemistry, Genetics and Molecular Biology

• Artificial Neural Network 33%