Article

Forward variable selection improves the power of random forest for high-dimensional microbiome data

2021-04-05

Abstract excerpt

<title>Abstract</title> <p><bold>Background</bold>: Random forest (RF) captures complex feature patterns that differentiate groups of samples and is rapidly being adopted in microbiome studies. However, a major challenge is the high dimensionality of microbiome datasets. They include thousands of species or molecular functions of particular biological interest. This high dimensionality significantly reduces the p...

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Literature Corpus work: f4575ad1-7d4a-5d9e-a4fd-c7a3f4c3bb0b
DOI: 10.21203/rs.3.rs-319022/v1

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