November 15, 2019Metabolomics180 citationsOpen Access

A comparative evaluation of the generalised predictive ability of eight machine learning algorithms across ten clinical metabolomics data sets for binary classification

KMKevin MendezBrigham and Women's Hospital SRStacey N. ReinkeEdith Cowan University DBDavid BroadhurstEdith Cowan University

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Key points are not available for this paper at this time.

Abstract

The size of the data set, and choice of performance metric, had a greater influence on generalised predictive performance than the choice of machine learning algorithm.

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Mendez et al. (2019) studied this question.

synapsesocial.com/papers/69d9e7ba0d540cafc5837eb0 https://doi.org/10.1007/s11306-019-1612-4

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November 15, 2019Metabolomics180 citationsOpen Access

A comparative evaluation of the generalised predictive ability of eight machine learning algorithms across ten clinical metabolomics data sets for binary classification

KMKevin MendezBrigham and Women's Hospital SRStacey N. ReinkeEdith Cowan University DBDavid BroadhurstEdith Cowan University

Key Points

Key points are not available for this paper at this time.

Abstract

The size of the data set, and choice of performance metric, had a greater influence on generalised predictive performance than the choice of machine learning algorithm.

Ask AI

Helpful

Bookmark

View Full Paper

Cite This Study

Mendez et al. (2019) studied this question.

synapsesocial.com/papers/69d9e7ba0d540cafc5837eb0 https://doi.org/10.1007/s11306-019-1612-4

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View Full Paper