Mining the forest: uncovering biological mechanisms by interpreting Random Forests

Abstract excerpt

Biological datasets are large and complex. Machine learning models are therefore essential to capture relationships in the data. Unfortunately, the inferred complex models are often difficult to understand and interpretation is limited to a list of features ranked on their importance in the model. We propose a computational approach, called Foresight, that enables interpretation of the patterns uncovered by Random...

Topics

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• Algorithms
• Classification
• Data Mining
• Family Health
• Genetic Diseases, Inborn
• Genomics
• Neoplasms
• Polymorphism, Single Nucleotide

Identifiers and source

Literature Corpus work

0e531962-f329-5585-a37e-c187e867ee30

DOI

10.1101/217695